Questions tagged [training]
Training is the part of machine learning whereby a model is "trained" on a define portion of a dataset to learn attributes and statistical features of the data. It's counterparts are called Testing and Validation. After training a model is tested and validated on another portion of the dataset.
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Final Model Training Problem - Overfitting
I am working on a CNN project for multiclass classification. I implemented hyperparameter optimization to find the most suitable model, during which I got a best accuracy of 97.38%. I then took this ...
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Data redundancy between train and test dataset - why is it bad (source needed)
I know that it is not OK to have too similar data in the train and test set (for example two pictures that differ by only one pixel). I'm trying to find a scientifically valid explanation why it is ...
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Does the Transformer model has memory to store the state accross different data injection sequences(segments)?
I've trained a transformer model based on the pytorch tutorial: https://pytorch.org/tutorials/beginner/transformer_tutorial.html,
But I found I've difficulties to understant this model's input and ...
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how can i store independent multiple time series datasets with same features in a matrix for training a model at once?
I have independent multiple time series datasets with same features. They are drilling proccesses in bone. Each dataset is a measurement. Is there a way to store all the datasets into a Matrix or ...
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Splitting data when combining multiple datasets
I have 13 small datasets from 12 different countries. All datasets have the same outcome and features, though have a different number of observations (ranging from ~50 to ~800). I would like to ...
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The weighted average ensemble model does not train on the whole data
I am using custom data generator. I want to apply weighted average ensemble. The training set has 1042 samples, and validation indicates 298 samples. The batch size is 64.
when I run this :
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Overfitted model [duplicate]
A classic question with an unclear answer, is it better to have an overfitted model performing better on a Cross-Validation setting, or a non-overfitted model performing worse?
In this context, higher ...
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How to label a transactions dataset made from scratch?
I have a question regarding creating a transactions dataset from scratch.
I've created customer profiles and am generating transactions based on these profiles. The way I do this is based on the ...
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ValueError: Found input variables with inconsistent numbers of samples: [283, 943]
I am trying yo split the data using train_test_split(), but I got this error:
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fine tuning open ai model with historical data
i'm trying to understand more about training models and unsure how to approach this problem.
I have a bunch of historical financial data that I would like open ai to use as additional context when ...
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How can someone build a dataset for a "propensity to purchase" model?
Ok, this might seem a trivial question for some and it's not even a question, more like a discussion. I read the rules and I believe it's everything fine, so I'm gonna take my chances...
Here's the ...
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unbalanced data on train set and test set
I already have 2 datasets. One to use for training and one for testing.
Both datasets are unbalanced (with similar percentages), with around 90% of label 1 .
Will it be useful to balance the data if ...
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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 ...
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Do model training pipeline should run on dev, staging and production environment?
I know it's a best practice to ship our code from dev to staging to production by including different level tests and validations that will help to confidently deploy on the production environment.
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Train/val/test approach for hyperparameter tuning
When looking to train a model, does it make sense to have a 60-20-20 train val test split, first hyper parameter tuning over the training dataset, using the validation set, picking the best model. ...
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Estimate train complexity of a Pytorch model
I guess there are better "keywords" than that, especially I'm not sure about the "complexity" word. But I thought of none.
Let's say I have a NLP model with 1. a Embedding Layer 2. ...
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How to extract values from unstructured text
I'm implementing a tool which should extract values of interest from unstructured text entries. The data set is several hundred thousands of medical entries. Each entry is relatively short (around 100 ...
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What approach can be take to design a food menu intelligently?
I am given following problem, for which I am seeking for advice.
Problem Statement
Suppose you are given a catalogue of dishes with their cost and calories. Can you design an algorithm/model which can ...
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How to do train-test split for multi-class classification
I am performing multi-class classification problem of different concentrations of Acetaminophen in a specified dataset. My data is in the form of images and I am using CNN. I have compiled all the ...
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Dynamically remove data from training dataset
I was wondering today if it would be a good approach to remove data dynamically from the training dataset when learning a neural network. Assuming a classification task, the approach would be ...
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Training an Object Detection Model from scratch vs. pretrained weights
I have a question related to training a object detection model:
Lets say I have trained a model for detecting 1 class with, say, 500 images including positive and negative samples and saved the best ...
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Should I drop duplicates over features but no target
I'm in a debate with someone about a problem where there are duplicates over features (i.e. $ X_1 = X_2 $ but $ Y_1 != Y_2 $).
My point of view is that we should keep those datas, as they can be ...
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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 ...
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Can the Apple M1's iGPU access the entire RAM as "video memory" when training with typical deep learning frameworks?
Can the Apple M1's iGPU access the entire RAM as "video memory" when training with typical deep learning frameworks (e.g., tensorflow_macos)? If not, what memory do they use as video memory?
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How to differentiate Bitmojis gender?
I have seen this Project Larry-zx's Githubproject
It is used to create a .pth file which can differenciate between a bitmojis gender.
Now I have created that .pth file but no idea how to use it, ...
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Train AI to recognize a Snapchat's bitmoji's gender
I have found this https://www.kaggle.com/competitions/bitmoji-faces-gender-recognition/overview/description competition. I need the file module that returns either male or female but cant find it. How ...
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DisableProfiler error on XGBoost fit
Suddenly, code that was working (before the Christmas break) now does not. I would like to know why. The documentation seems incomplete and the error message is cryptic in context.
On trying to fit a ...
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Test score higher than train score
I implemented a Gaussian Naive Bayes classifier and I got a test score (99,99%) higher than the train score (96,87%)
Is this normal or does it mean that my model is underfitting ?
Thank you.
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Training Dataset preparation for customer Churn at a specific Month
I have dataset of customers from 2019-2022 . My goal is to predict customer Churn at a specific point in time , say exactly 3 months from the observation point ...
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Evaluate a Recommender System based on the data between two months
currently my company's planning to use a new Recommender tool/library for a book website, and now we want to compare the result between these two tools (both of the tool use Universal Recommender ...
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Ensuring memorization doesn't happen between between train and test sets in a Machine Learning model
Recently, contractors developed an NER solution for us which extracts relevant drugs out of pharmaceutical policies (drugs that the policy was describing coverage criteria for). Part of their process ...
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Time-series feature enrichment before or after train-test split?
I am dealing with a time-series that represents the CPU usage registered on Azure Virtual Machine. The historical data include a period of 19 months and its granularity is a 10 minute one (each 10 ...
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Is it possible to turn the gmail inbox into a dataset for AI fine tuning?
My idea is to have a dataset of my gmail emails and replies. The purpose is to create a bot that can reply new emails based on all past correspondence in my inbox. How do i prepare such dataset from ...
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When using custom metrics, num_threads setting is not working in lightgbm?
When I train a lightgbm model with my own custom metrics, I find that model is trained in single thread, though I set "num_threads": 16.
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How to use my resampled data (through SMOTE) for my models?
I'm quite new to Python coding so maybe this is an obvious thing.
I am dealing with an imbalanced data set. I have encoded the categorical features and transformed them into numpy.array. After this, I ...
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Training tricks for increasing stability in mixed precision
I would love to be able to use automatic mixed precision more extensively in my training, but I find that it is too unstable and often ends in NaNs. Are there any general tricks in training that ...
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C Drive got filled while training my dataset over yolov5
Asked the question over a cross-validated stack but got recommendations to ask at the data science stack. So, I recently bought a GPU and tried yolov5 on my personal dataset of around 1500 images. ...
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How to carry metadata with data examples and labels in python?
Is there a pythonic way to carry around metadata that describes the training examples, such that it preserves (i.e., order) after shuffling and splitting (train/test)?
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How to train AI to recognize a Snapchat's bitmoji's gender
I would like to enable my Python script to get a vague idea of a bitmoji's gender.
I found these two git repositories that are able to differentiate between them.
How would I use them to have my ...
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why it would be improper to compute and use test set means?
I have 2 questions regarding the whole subject of the data set in machine learning and I would be happy to receive an answer :)
1.Why it would be improper to compute and use test set means and ...
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kernel initializers and epochs
In a sample code like this (From Keras library):
model.add(Dense(13, input_dim=13, kernel_initializer='normal', activation='relu'))
the kernel values will be ...
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Trying to make a visualization for training performance
I am using scikit learn's BayesianRidge model to fit a regression to tabular data of d features and N sample. I have already tested how well my model performs using a repeated kfold cross validation ...
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Predictive value of short text fields
I am working on a classification model using one of the following three algorithms: RandomForestClassifier, a TensorFlow model and a LogisticRegression model.
The data set I am working with has a ...
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How does sklearn random forest use features in the form of 1D/2D array instead of a single value during splitting at a node?
For the training of random forest model in sklearn, I understand that for features of a single value, a threshold for splitting the data is determined by minimizing the Gini impurity or maximizing ...
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What does that mean if the loss looks like this?
I have a problem. I have trained a model. And as you can see, there is a zigzag in the loss. In addition, the validation loss is increasing.
What does this mean if you only look at the training curve? ...
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In Orange Data Mining, how do I use results from clustering a training-set to test and score a test-set?
I am performing analysis on the well-known 'Adult' data-set, available on UCI using Orange Data Mining. In a PhD thesis, Pelleg (2004; pg 79) uses unsupervised clustering of the prescribed training ...
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Why should you decide a re training of a machine learning model by a conversion rate or KPI and not randomly or according to perodic time?
Why is it more beneficial to automatically train a machine model by a conversion rate or by a KPI instead of by periodic time?
The following image shows an example of the conversion rate. However, as ...
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Developing Modified KNN Approach
I want to divide the training set into n partitions further besides testing set. How can I do that?
Furthermore, I'm creating these groups in the training set. How ...
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Can we train of a binary classifier with "A" to classify "a"?
I have a maybe naive question about the appropriateness of using binary classifications. This is a hypothetical example, so forgive me if it is too coarse.
Let's say I want to train a support vector ...
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Is it ok to separate data to train on different time instead of putting all in one go?
So let say i have 10,000 images ready to be trained on. But my GPU cannot handle all of that.
So the questions is:
Can i train the model 10 times with 1000 images each time, with same epochs and ...
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