text stringlengths 83 79.5k |
|---|
H: Predicting probability of reaching a milestone -- How much data should I use from production universe to train/test model?
If I am predicting probability of a business to reach (x) milestone (classification 1), but the only data I have is live production data, how much of the production data should I use to train t... |
H: In DBSCAN, can the distance between a Noise Point and Border Point be less than Epsilon?
In DBSCAN:
A core point is a point which has at least "MinPts" points inside its Epsilon radius.
A border point is a point inside the Epsilon radius of a core point, but it has a number of points inside its own Epsilon radius ... |
H: What is the best way to use three different losses on two classifiers?
Two classifiers need to be trained simultaneously, and I have three losses, as shown in the figure. Classifiers 1 and 2 will be updated by losses 1 and 2. Furthermore, loss 3 should update the two classifiers concurrently.
Here's what I did
loss... |
H: NLP vs Keyword-Search. which one is the best?
I have constructed a natural language processing (NLP) model with the aim of identifying technology keywords within text. The model is trained on a large dataset that contains over 400,000 phrases and has been annotated with approximately 1000 technology keywords, of wh... |
H: Total Retention Rate Calculated from Categories
I am calculating retention for 3 categories and then total, and I am trying to double check my total, but my check formula isn't working.
I am comparing the last 14 days (let's call it Period 1) to the 14 days before that (let's call it Period 2).
I am using the follo... |
H: Train test split before or train test split inside cross validation
I want to do cross validation. So should i split my data into train and test with sklearn train_test_split and use cross validation like this:
cross_validate(model, X_train, y_train, scoring = roc_auc, cv = 5, n_jobs = -1)
Or should i make a funct... |
H: How is weight matrix calculated in a neural network?
Context: I am a pure mathematician trying to understand machine learning. I am studying it from various sources, now focusing on NLP and word embeddings.
My question: What is the weight matrix for a neural network? How is it calculated, in layman terms? (Or even ... |
H: How to automatically classify a sentence or text based on its context?
I have a database of sentences which are about different topics. I want to automatically classify each sentence with the one or more relevant tags based on the context of the sentence as shown below:
Sentence: The area of a circle is pi time the... |
H: DecisionTreeClassifier cannot take one-hot encoded classes?
I got ValueError: Found array with dim 3. None expected <= 2. I dont know which array has dim 3?
DecisionTreeClassifier cannot take one-hot encoded classes?
But from this page it should support? https://scikit-learn.org/stable/modules/multiclass.html
labe... |
H: Should highly correlated features be removed, even if they have different type of information?
A quick example for this: we have many feature and two of them are policy count and premium_total (for all policies). We are predicting the expected claim amount with GBM or RF. Both policy_count and premium_total are imp... |
H: Normalization / Overfitting Issues
I have a dataset with 608 inputs and I'm trying to output a single 1 or 0 result. My validation data has 69.12% 0's. When ran, my model always returns 69.12% accuracy, presumably because it's "good enough" given the imbalance in the validation set. I've added an input normalizatio... |
H: Best package and function in R to use to replicate my (Backward & Forward) Stepwise Regression results I got using step from the stat package
I am doing a research project as a 2nd author on a paper exploring the properties of a novel algorithm for Optimal Variable Selection where I am running the benchmark Variabl... |
H: LSTMs how to forecast out N steps
I have about 3 weeks of 15 minute building electricity power data and curious to know how can I predict an entire days worth of electricity into the future? 96 Future values that makes up 24 hours...my model only outputs/predicts 1 step into the future any tips greatly appreciated ... |
H: What is the purpose of EarlyStopping returning last epoch's weights by default?
I recently realized that keras callback for early stopping returns the last epoch's weights by default. If you want to do otherwise you can use the argument restore_best_weights=True, as stated for example in this answer or documentatio... |
H: Requirements for variable length output in transformer
I have been working on modifying the transformer from the article The Annotated Transformer. One of the features I would like to include is the ability to pass a sequence of fixed length, and receive an output sequence of a shorter length, which is possible per... |
H: Why is monotonic constraint disabled when using MAE as an objective to LGBM?
I tried to use monotonic constraints in LGBM, but if I use mean absolute error as an objective, it gives a warning that monotonic constraints cannot be done in l1.
What is the reason? Thanks!
AI: MAE is an odd loss function for GBMs: the g... |
H: NLP topic clustering
In my dataset, I have 500 abstracts. The goal is to cluster them in 2 topics.
One topic must have those abstracts which contain some list of words or similar words and the rest of the abstracts in other topic. Can anyone kindly offer me suggestions to do this?
AI: for clustering the abstracts, ... |
H: Get the value of second dimension in numpy array
My NumPy array looks like this
array([-5.65998629e-02, -1.21844731e-01, 2.44745120e-01, 1.73819885e-01,
-1.99641913e-01, -9.42866057e-02, ..])]
['آؤ_بھگت'
array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., ... |
H: How to perform a classification experiment with data augmentation?
I'm working on an audio classification experiment. In my original database, I have 1,412 records. To improve the performance of my models, I resorted to data augmentation, applying simple techniques such as noise addition and pitch reduction.
After ... |
H: Why are the hidden states of an RNN initialised every epoch instead of every batch?
Why are the hidden states of RNNs/LSTMs/GRUs generally re-initialised only once an epoch has finished, not once a batch has finished?
AI: Hidden states of an RNN are initialized every epoch ONLY if you are using truncated back-propa... |
H: Do I need to use always the same "Test" dataset to compare between different models?
I have two datasources A and B, and I want to check how several methods can affect the accuracy of my multi class models:
If I use cross-validation with validate dataset to obtain the best
hyper parameters.
If I inject more data f... |
H: Which word embedding mechanism does chatGPT use?
Which word embedding mechanism does chatGPT use? Is it Word2Vec, GloVe, or something else?
AI: ChatGPT is a language model based on the Transformer neural architecture, but only the decoder part.
It does not use pre-trained embeddings to represent text. Instead, the ... |
H: Change the shape of numpy array
My numpy array has the shape of (99,2) basically it has 2 columns one is the word and the other is a hot encoding vector size of 300 I want to delete the column of words and want to have only encoding vectors
in order to delete I have to use the simple line of code
arr = np.delete(x,... |
H: problem on converting data to numpy array
I have pandas data frame
data=df.loc[[0]]
print(data)
0 3.5257,3.5257,3.5257000000000005,3.5257,3.5257...
Name: testdata, dtype: object
I need to convert it to numpy array and want to plot the figure
AI: You can use the .values attribute of the dataframe to convert it ... |
H: How to present a statistical justification for the choice of models with approximate accuracies?
In an experiment involving the comparison of classification algorithms, how can I assess whether there are statistically significant differences between the analyzed models? For example, the following models were tested... |
H: Append prediction of tensorflow to a pandas dataframe
I built a tensorflow model to make text classification in four category, after testing and evaluating it, I need to apply it to actual data to predict the class of them, I create a predict function that return the probability of each class that this text can be.... |
H: GAN Generator Backpropagation Gradient Shape Doesn't Match
In the TensorFlow example (https://www.tensorflow.org/tutorials/generative/dcgan#the_discriminator) the discriminator has a single output neuron (assume batch_size=1).
Then over in the training loop the generator's BinaryCrossentropy loss is calculated usin... |
H: ML Predicted Model for 2 values
I have a data set with 96 rows. It contains date, source, spend and number of customers.
I have 4 different sources that generate customers and you can see in the dataset how much I spend and how many customers I have received by month for the last two years.
I have a budget for 2023... |
H: How to calculate accuracy of a logistic regression?
A logistic regression involves a linear combination of features to predict the log-odds of a binary, yes/no-style event. That log-odds can then be transformed to a probability. If $\hat L_i$ is the predicted log-odds of observation $i$, then define the predicted p... |
H: What is the dataset during testing a Variational auto-encoder?
I am getting confused in the testing dataset of a VAE. After training the VAE, what should be the testing data-set of the VAE?
I understand that during testing the VAE only has the decoder part. Hence, we need to give inputs from the latent space. But w... |
H: Binary Classification [Text] based on Embedding Distance?
I was just informed this community was a better fit for my SO question. I am wondering if I can use a Milvus or Faiss (L2 or IP or...) to classify documents as similar or not based on distance. I have vectorized text from news articles and stored into Milvus... |
H: The ideal function in R for fit fitting n LASSO Regressions on n data sets
As part of a statistical learning research paper I am collaborating on, I am running/fitting two hundred sixty thousand different LASSO Regressions on the same number of different randomly generated synthetic data sets and calculating some s... |
H: Best practices for serving user-specific large models in a web application?
First execuse any naive statement you may find below, i'm a newcomer to the field.
How do web applications that integrate fine-tuning of large machine learning/deep learning models handle the storage and retrieval of these models for infere... |
H: how can I translate Whisper encodings to SBERT embeddings?
I'm using the Whisper model to recognize speech, and then matching the output text against a list of known questions by generating SBERT embeddings from the text and ranking the known questions by cosine similarity with the SBERT embeddings of the text outp... |
H: Visualizing convolutional neural networks embedding
In this article, the author creates a graph (at the end of the post) from the embeddings of different words found by transformer model. I would like to do a similar thing for a convolutional neural network in order to be able to evaluate clusters. The final object... |
H: Timeseries (InfluxDB): How to deal with missing data?
Question Description
We are performing a lot of timeseries queries, these queries sometimes result in issues, they are usually performed through an API (Python) and sometimes result in complete failure due to data missing.
Due to this situation we are not sure w... |
H: Topic classification on text data with no/few labels
I would like to achieve a classification of a text input into predefined categories.
From what I have understand unsupervised approach are unfeasible if my target label is something very rare in pretrained models (I have labels about specific industrial processes... |
H: Which is the loss function used for validating a CF Recommender System?
I am developing (from scratch) a memory-based CF Recommender System based on movielens dataset.
My CF RS uses a URM (User Rating Matrix) where r_ij contains the rating the user i gave to movie j (or missing).
I am given a test set. Moreover I a... |
H: Train question answering model with custom dataset
How can I train a question-answering ML model with a custom dataset?
I have gathered nearly 110GB of text data, containing documentation manuals for software products and I am looking into different ML algorithms for question-answering.
The problem is that I don't ... |
H: Can I use a fitted polynomial regression to make reverse predictions?
I want to start off by acknowledging that this may be a dumb-sounding question to someone with more machine learning experience to me, so please go easy. Here is the background. I am currently an undergraduate assisting with research/development ... |
H: What loss function to use for predicting discrete output sequence given a discrete input sequence?
I am working on sequence-to-sequence tasks where the input is an n-length sequence of discrete values from a finite set S (say {x | x is a non-negative integer less than 10}).
An example input sequence of length 5 is:... |
H: Alternatives to Toronto Book Corpus
As the toronto book corpus is no longer available (or rather, only in lowercase), I am looking for an alternative dataset of comparable language variety, quality, and size.
Any suggestions? The Gutenberg Standardized Corpus is too big and still requires lots of preprocessing.
AI:... |
H: Best way to detect newly incoming anomalies in two timeseries?
I have two devices that both send data (let's say temperature). I need to be able to detect if one of the devices reports an unusual/anomalous reading. The case if both of the devices report a "weird" value doesn't need to be handled. So, for example:
D... |
H: Words limit using GPT-3 API and fine tune model
In the documentation for GPT-3 API, it says One limitation to keep in mind is that, for most models, a single API request can only process up to 2,048 tokens (roughly 1,500 words) between your prompt and completion.
In the documentation for fine tuning model, it says ... |
H: Why is the accuracy on train dataset not always 100% while we use the same dataset to train the model?
Though tree-based ML algorithms give us 100% accuracy on train dataset many times, but why is this not happening every time. I know this results in overfitting but why not 100% accuracy every time on the dataset u... |
H: How train a pre-trained model based on new dataset?
I have trained a deep nn model based on some existing data. In the meantime, I have collected more data and label them so that I can feed it to the model to improve its performance. The questions is, should I feed:
Option 1- New data to the already trained model?
... |
H: polars: parsing a funky datetime format with optional fields
I am trying to handle data coming from software that has as a terrible format for a time duration: [days-]hours:minutes:seconds[.microseconds]. In case someone else has already traveled this path, I'm fighting with the Elapsed and field from SLURM's sacct... |
H: How can I be more certain that I have not accidentally made my ML model predict on training data?
I have this random forest model setup as shown below in python. It's performing unexpectedly well with a ~70% classification success rate (to the extent where I really doubt it is genuine) and I am therefore skeptical ... |
H: Solve optimization problem with machine learning algorithm
I have an optimization problem that I solved with grid search using hyperopt in python. In this problem, I have some parameters and a score. I want to find the best parameters that maximize this score. Until now, I didn't see any machine learning algorithms... |
H: time series forecasting with two columns
I have a task which is time series forecasting with two columns
to predict Number_of column. so I wonder what is the approach to deal with these two time series to predict Number_of column.
AI: This seems to require a model for a univariate time series. The Date-column is ... |
H: estimating coordinate correction
I'm working with 3d coordinate data (x,y,z), however I know that the z coordinate is systematically wrong and the error of z is dependant on both x and y. I however do have some data where I know the correct z value so I want to make a model that can given the xyz coordinates give ... |
H: What ML techniques could be used for biometric feature extraction and ID generation?
I'm working on a project that involves generating a unique ID for a given biometric (such as an iris image). I'm interested in exploring the use of ML techniques for feature extraction and ID generation. Specifically, I'm intereste... |
H: Sentiment analysis BERT vs Model from scratch
I am working on building a sentiment analyzer, the data I would like to analyze is social media data from twitter, once I have created a the model I want to integrate it into a simply webpage.
I have tried two options:
Create my own model from scratch, meaning train a ... |
H: how to build an images dataset efficiently
I have several image datasets and I am going to combine all of them into 1 giant dataset I decided to load the images which are in different formats (SVG, PIL images, etc ) and save them as png but this took forever, there any alternative solution?
AI: Yes,
You can use Ima... |
H: pl.datetime plots as days since epoch or 1970, if formatted - polars and matplotlib
I'm attempting to port some old reports from Pandas to Polars. I am happy with the data, and am now attempting to plot a few time series. This is working, but I'm finding that matplotlib just doesn't seem to want to cooperate with P... |
H: How to treat categorical columns after ordinal encoding?
If encode three categorical variables like "bad", "normal", "good" into 0,1,2, after that can I treat them as numerical values? So can I perform on them MinMaxScaler or RobustScaler? Or, since they are from categorical values, I must leave them like 0,1,2.
Th... |
H: Is there a way to use debt details without aggregating them to predict the probability of payment of every debt per debtor?
I edited my post for clarity, for the second time. Thx lpounng for the feedback.
I am seeking advice on predicting debt payment within a year. Each debt has its own carachteristic wich are not... |
H: What are the advantages of autoregressive over seq2seq?
Why are recent dialog agents, such as ChatGPT, BlenderBot3, and Sparrow, based on the decoder architecture instead of the encoder-decoder architecture?
I know the difference between the attention of the encoder and the decoder, but in terms of dialogue, isn't ... |
H: Machine learning / statistical model of a deterministic process: how large must my training set be to ensure almost perfect accuracy?
This may be a silly question, but if I got a deterministic process, for instance, a function (in the mathematical sense) that happens to be computationally expensive to evaluate, and... |
H: Which intrinsically explainable model has the highest performance?
Explainable AI can be achieved through intrinsically explainable models, like logistic and linear regression, or post-hoc explanations, like SHAP.
I want to use an intrinsically explainable model on tabular data for a classification task. However, l... |
H: Self-attention in Transformers, are the component values of input vector trained or is it the set W_q, W_k, W_v?
By far, I find this tutorial on self-attention the most digestible (https://peterbloem.nl/blog/transformers)
Still, I got a question from reading there, hopefully, you guys can help me out
Are the com... |
H: How can I calculate FPR?
How can I compute the FPR for sentences with no labels?
Is there any relation between the FPR and the likelihood?
AI: By definition, you must have labels to compute the false positive rate (FPR). If you don't have labels, you can't possibly compute it, because you don't know if the positive... |
H: Understand the interpretability of word embeddings
When reading the Tensorflow tutorial for Word Embeddings, I found two notes that confuse me:
Note: Experimentally, you may be able to produce more interpretable embeddings by using a simpler model. Try deleting the Dense(16) layer, retraining the model, and visual... |
H: What else can I do to help my model my classification task?
I have a classification task that I'm currently getting really low accuracy metrics on (my highest accuracy score is about 20%). So far I've run 5 models: quadratic disc analysis, logistic regression, knn, random forest, and naive bayes (Gaussian but will ... |
H: Determining "filters" dimension after a convolution operation
I tried to calculate the "filtered" dimension and I seem to be getting it wrong.
Below there is the image I am trying to calculate the "filtered" dimension for, where you have 192 of depth, and the operations applied are 3x3x192 conv, and 2x2-s-2 MaxPool... |
H: What does the output of an encoder in encoder-decoder model represent?
So in most blogs or books touching upon the topic of encoder-decoder architectures the authors usually say that the last hidden state(s) of the encoder is passed as input to the decoder and the encoder output is discarded. They skim over that to... |
H: How do you retrain a model as new data comes in?
I'm just curious about real ML projects on production.
I was wondering what is the way to go to retrain your models when you get new data? for example, let's suppose you've built a model with 2023 January data. When February's data comes in, do you have to either ret... |
H: What is exactly the input to a second lstm layer?
I am often confused about the lstm with more than one layer.
Imagine i have two lstm layer with 3 cells each layer.
What is exactly the input to the second lstm layer ?
AI: The input to the second LSTM layer is the output at each time step of the first LSTM layer. |
H: Trying to extrapolate info from a partial data set - statistical inference
I am wondering if my logic is OK here or not.
98% of a group without a device has an event occur
2% of group with device has an event occur
Since we know that correlation isn't causation I can't say that the device made a difference one way ... |
H: OpenCV add/subtract functions produce different results from numpy array add/subtract
Im trying to brighten and dim an image using OpenCV with two approaches.
Approach 1: Used OpenCV's add and subtract functions to brigthen and dim the image.
Approach 2: Manually added/subtracted pixel values.
Both produced differe... |
H: Is it cheating to use normal KFold for data that is collected over time?
I am in doubt when to use strict time-series cross validation and when to use kfold. I have the following situation, which, I believe, is an edge-case between time series and normal data:
I have a small dataset which is a couple of thousand ro... |
H: Survey on image retrieval datasets
I am on a survey about image retrieval datasets. I have found some, such as:
NUS-WIDE
Oxford5k
Oxford105k
Paris6k
MSCOCO
I have been way too confused about the detection metrics and the metrics they use inside these datasets for image retrieval purposes. For example:
AP
Recall
... |
H: Are there any pre-trained non english model of deepspeech?
I want to try deepspeech model.
I founded only english pre-trained model
Are there any other pre-trained not english model of deepspeech ?
AI: You can check Coqui, a fork of Mozilla DeepSpeech created by former Mozilla DeepSpeech developers. It is well main... |
H: What values are actually used for the kernel when using a Conv2D layer?
I'm currently trying to fully understand what a Conv2D layer actually does and I think I got most of it. But theres one thing I don't quite get. When reading about Kernels there were multiple mentions that for example a (3,3) kernel, like this ... |
H: Group rows partially [Python] [Pandas]
Good morning everyone.
I have the following data:
import pandas as pd
info = {
'states': [-1, -1, -1, 1, 1, -1, 0, 1, 1, 1],
'values': [34, 29, 28, 30, 35, 33, 33, 36, 40, 41] }
df = pd.DataFrame(data=info)
print(df)
>>>
states values
0 -1 34
1 -1 ... |
H: What does Codex take as tokens?
The typical default for neural networks in natural language processing has been to take words as tokens.
OpenAI Codex is based on GPT-3, but also deals with source code. For source code in general, there is no corresponding obvious choice of tokens, because each programming language ... |
H: Patterns extraction in time serie with DTW
I have a long time serie, let's say 1000 items. I want to find patterns in it of different lengths from 10 to 100 elements.
To do this, I extract sliding windows of different lengths and calculate distance matrix between them using DTW. But it works very slowly.
Can you pl... |
H: Is it meaningfull using boxplots for representing the distribution of just four data points?
I'm using boxplots for representing the distribution of some datasets. In one of these datasets I have just four data points. Is it meaningful using boxplots for representing the distribution of such a small sample?
AI: Thi... |
H: using a feature that is only available during training
I'm working on a project that aims to classify JIRA issues into their relevant owner group.
An issue has the following text features:
Summary
Description
Comments
all of which are text based.
During prediction time, however, no comments are available as the g... |
H: What's the fastest clustering package in Python?
I'd like to perform clustering analysis on a dataset with 1,300 columns and 500,000 rows.
I've seen that clustering algorithms are available in SciKit-Learn. But I'm worried that the algorithms will be inefficient on a dataset of this size.
Is SciKit-Learn slow, and,... |
H: Force network to weigh specific variables during learning
I have a pandas data frame containing around 100000 observations of plant species and their age with additional numerical predictors (climate). I used tensorflow and keras to build a sequential model to predict species age. Here is the code for my basic regr... |
H: How to read colon in python?
My course has the following statement.
a = np.array([[3, 2, 5], [1, 4, 6]])
We select all columns of a matrix where the entry on row 1 is greater
than the entry in row 0
a[:, a[1, :] > a[0, :]]
I am confused about the colon being in the first position to mean "select all columns" an... |
H: Pytorch mat1 and mat2 shapes cannot be multiplied
The error message shows
RuntimeError: mat1 and mat2 shapes cannot be multiplied (32x32768 and 512x256)
I have built the following model:
def classifier_block(input, output, kernel_size, stride, last_layer=False):
if not last_layer:
x = nn.Sequential(
... |
H: Random Forest on high correlated data
I am relatively new on data science sector. I started tampering with random forest models and some strange occasions aroused. To be precise, I have data from sensors that record pollutants and a column that acts as the labels populated with data that shows if a person has devel... |
H: Which chess notation to feed neural network: FEN or PGN?
I am trying to build a chess AI with a neural network. To learn about how neural networks work and refresh my programming experience. I have some experience with classifiers but not yet with neural networks, so feel free to correct wrong assumptions and mista... |
H: Multiple classes present in one-hot encoding
When dealing with classification for multiple classes present in the same sample, can the output layer have the form of one-hot encoding, but instead of only one hot, have multiple?
That is, in case of a only single class being present in the sample, the encoding could b... |
H: Seasonal ARIMA?
Greatly enjoy exploring data in Orange Data Mining!
I have daily average temperature data for several years. I can plot the periodogram, and do a seasonal decompose.
Is there a way to forecast the temperature using SARIMA?
I tried using ARIMA with moving average order (q) = 70 (the max possible). I... |
H: How to split a single feature vector into a layer of 2 neurons
Given an array x = [1, 2, 3, ...] , I want to split each sample x[i] into 2 neurons.
My idea was to initialize a variable split = np.random.rand() with $0 < split < 1$
and then set the neurons x1 = split * x[i], x2 = (1 - split) * x[i].
Is my idea corre... |
H: ReLu layer in CNN (RGB Image)
I am able to get convoluted values from RGB Image lets say for each channel.
So I have red channel with values: -100,8,96,1056,-632,2,3....
Now what I do is that I normalize this values in range 0-255 because that is range of rgb values basically with code Math.Max(minValue, Math.Min(m... |
H: Why two different series of SQL queries which do the same thing just in a different order have a different number of rows in their outputs?
I am working on a group project for the US Forest Service to create a dashboard on the US's arial firefighting operations and resources. This part is focused on creating a sing... |
H: The difference between Faiss Index and a Database Index
An index points to data in a table. In a database, indexes are similar to those in books. I am a little bit confused about the meaning of index in Faiss library and how it's different from the one in the database please if possible?
AI: TL;DR;
FAISS Indexation... |
H: How to bias a neural network towards one category in binary classification?
I have a basic sequential neural network built with TensorFlow.
model = tf.keras.Sequential([
Dense(16, activation='relu', input_shape=(X_train.shape[1],), kernel_regularizer=l1_l2(0.001, 0.001)),
Dropout(0.3),
BatchNormalizatio... |
H: Why does BLEU score for ignite, torchmetrics and nltk differs?
Here is the example :
from ignite.metrics.nlp import Bleu
from nltk.translate.bleu_score import sentence_bleu
from torchmetrics.text.bleu import BLEUScore
references = [['the', 'quick', 'brown', 'fox', 'jumped', 'over', 'the', 'lazy', 'dog']]
candida... |
H: Do models of social systems suffer from prediction drift?
Background
I've created a binary classification model that predicts the probability of fraud for a given sample.
The choice of threshold allows me to set how many frauds are captured in the training dataset. However, when I test the model on a similar datase... |
H: Why does Logistic Regression perform better than machine learning models in clinical prediction studies
I am developing binary classification models to predict a medical condition in my dataset. My results show that both Logistic Regression and Linear SVM consistently outperformed other ML algorithms (SVM, NB, MLP ... |
H: What techniques are used to analyze data drift?
I've created a model that has recently started suffering from drift.
I believe the drift is due to changes in the dataset but I don't know how to show that quantitatively.
What techniques are typically used to analyze and explain model (data) drift?
Extra:
The data is... |
H: GPT-2 architecture question
I am currently working on a NLP model that compares two comments and determines which one would be more popular. I have already came up with an architecture - it will be based on GPT-2. But now I am struggling understanding what is the general format of an output of it. I inspected this ... |
H: Convert cosine similarity to probability
In natural language processing, the cosine similarity is often used to compute the similarity between two words. It is bounded between [-1, 1]. Supposedly, 1 means complete similarity, -1 means something like antonyms, and 0 means no relationship between the words, although ... |
H: Making a netcdf data using xarray
I am very very new to the world of data science as I only started using it in my new job so I would really appreciate help from the community experts (maybe also in simple words :)).
I am trying to build a dataset comprising data extracted from a NetCDF data file. The data extract ... |
H: moments of weight vectors in Adam
When performing backpropagation with Adam algorithm, are the moment and the second moment of the weight vectors calculated also for the weights in hidden layers?
AI: It looks like it.
The equations in the description of the algorithm in Hands-on Machine Learning as well as the orig... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.