Questions tagged [train]

Training (or estimation) of statistical models or machine learning algorithms.

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34 views

Is this K-Fold Cross-validation approach correct?

I've seen that Train-Validation-Test set technique is discussed and there is no consensus. Some people don't differ validation from test. When I was studying this technique and K-fold cross-validation,...
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10 views

Continuation of Training for Neural Networks

originally posted in SO Artificial Intelligence, advised to post here instead Background I am developing a GAN model (based off this paper), and am trying to learn how to feed subsequent time series ...
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21 views

How does test_size relate when used in python sklearn for a 10 fold cross validation [closed]

I am trying to implement a ML algorithm in which I would like to use a 10 fold cross validation process but I would just like to get confirmation if my procedure is correct. I am doing a binary ...
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21 views

Stratified sampling - use of proxy variable

For splitting of the data into train/test/val I use stratified sampling. Is it appropriate to define strata using information extracted from the dataset? E.g. use machine-learning to model proxy ...
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1answer
25 views

Time Series Forecasting Process With Regard to Training and Test Sets

I'm a bit confused about the process order in doing proper time series analysis/forecasting. Is it: Stationary/seasonality checks, do any transformations required Candidate model selection using ACF, ...
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14 views

Recurrent neural networks with loss of data

I want to train a recurrent neural network (RNN) for making predictions of some data. I have 8 variable inputs and with them I have to make predictions of other two variables (outputs). I need RNN to ...
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10 views

How does glmnet in caret choose the values of lambda and how does it compute coefficients of the model?

I have a question that I've been struggling with. My students are asking me, but I can't figure it out myself. When I train LASSO regression in R caret, I use the method "glmnet" and a grid ...
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10 views

Training in steps has any importance?

I'm trying to train a Siamese network for face Verification and eventually I came across the Contrastive Loss method for embedding vector distancing (kinda... I ...
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10 views

How do you use a weight matrix used for a batch in a final model to only take a single input?

Setup: An input vector x to a neural network has 5 components, xi, i=1,5. Say a weight vector is multiplied by x, w = [wi], i=1,5: so dot(w,x) = sum_i (wi * xi) Now when doing batch training, say 10 ...
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5 views

Validation Loss gets better after adding Augmentation Layers but Test accuracy gets worse

I'm building a Siamese Network which should learn a face comparison function. My model consists a CNN (which gets 2 inputs, and yields 2 embedding vectors). With the outputs I calculate: ...
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10 views

The implication for using only data points with extremely positive and negative labels for classification

Here I use the Quora dataset from Kaggle to explain my question. The label column of this dataset is is_duplicate and has value of 0 or 1. 255,043 question pairs in the dataset are labeled as 0(not ...
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20 views

How to improve model generalization with small dataset?

I have a fairly small dataset (45 data points (i.e populations) where I took plant information. I'm running a random forest regression on my measurements and climate information to predict a feature, ...
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1answer
71 views

About Epochs and how many of it?

I'm pritty new to the machine learning world, and I ws trying to figure out how many epochs should I run my training CNN model on the MNIST dataset (which has 60,000 training images and 10,000 ...
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1answer
42 views

Loss values above 1.0

I have a convolutional neural network for tensors classification in Pytorch. I am using Cross-Entropy Loss. My optimizer is Stochastic Gradient Descent and the learning rate is 0.0001. The accuracy of ...
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1answer
44 views

Train/Test split in multiple time series data

Currently, I have log files from 10 machines. Each log file contains an event type and the occurrence time of the event. Each machine's log file is recorded under the same time frame, and I wish to ...
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2answers
135 views

Why validation accuracy is increasing very slowly?

My convolutional network seems to work well in learning the features. However, the accuracy of the validation set is increasing very slowly with respect to the learning rate as also illustrated in the ...
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16 views

When training data is much less than the prediction perdio

Given training data on tweets and their retweets, how would you predict the number of retweets of a given tweet after 7 days after only observing 2 days worth of data? Its strikes me that this ...
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1answer
15 views

Does training time of CNN includes the validation time performed after every epoch?

I want to record train time of a CNN architecture in keras. My question is that while we are training a CNN, we also validate the model after every epoch to monitor that how well it generalizes which ...
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13 views

Correct way to use cross-validation for hyperparameter selection when testing a model in multiple trials which use different train-test split

I'm going to evaluate a model with some benchmark datasets. I want to perform 100 trials of training and testing of the model for each dataset, and I want to randomly split the data again in training ...
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1answer
276 views

How to choose a batch size and the number of epochs while training a NN

After searching I read diferent theorys that using a greater batch size has better performance while model is training, but in the other hand, I also find the oposite view, that using a mini-batch ...
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2answers
98 views

MultiClass Classification - Training OvO and OvA

I like to know how OvO (One vs One) and OvA (One vs All) models are trained in multiclass classification problem. To keep it simple, we have 4 classes, each of which has 1000 datapoints. What are the ...
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2answers
81 views

(How) can model parameters be learnt using MCMC?

I get stuck by part (b) of figure 4 in this paper: Hands-on Bayesian Neural Networks - a Tutorial for Deep Learning Users. In my understanding, inference algorithms like MCMC are not for training ...
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21 views

Why is the Kernel Trick Matrix Symmetric Even When the Training and Test Set Differ in Size?

Ridge Regression can be expressed as $$\hat{y} = (\mathbf{X'X} + a\mathbf{I}_d)^{-1}\mathbf{X}x$$ where $\hat{y}$ is the predicted label, $\mathbf{I}_d$ the $d \times d$ identify matrix, $\mathbf{x}$ ...
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27 views

Random forest outside range of training - Alternatives?

Statistical models in general are not well suited for applications outside the training range. Using a random forest binary classifier aimed at detecting an event, I've trained it using 100 data ...
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2answers
2k views

Can I (justifiably) train a second model only on the observations that a previous model predicted poorly?

Say I commit the following sins while building a predictive model: I take my dataset and split it into four subsets: Three for training (Train_A, Train_B, and Train_C) and one for validation. I ...
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6 views

What is the training process of 1 input - 2 output network based on one mixed loss?

Let's say I have a neural network with one input, 2 output layers, 1 hidden layer. I define a combined loss based on the first and second output. For simplicity, assume that the first loss is RMSE and ...
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21 views

Training Individual-Level Predictor using Distribution of Group-level Data

I have a problem in which I'm looking to train an individual-level predictor for outcomes. I have information on individual-level covariates, but I don't have individual-level outcome variables. ...
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2answers
33 views

What are best practices around combining train/val/test splits when training a production model?

Say I'm training a deep neural network and I have split my data into train, val, and test splits. I have trained many models on the train data and then using the val data during the training loop for ...
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2answers
135 views

Split data into test, training and validation when some patients have multiple observations

I have a dataset that has multiple observations for some patients. Patients are labelled by patient IDs and I would like to split the data into testing, training and validating groups as I am trying ...
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37 views

How to force a neural network to uniformly decrease MAPE?

I aim for replicating an numerical (non stochastic) algorithm by a neural network. Therefore I have basically an unlimited amount of data and I wish that the network have an almost perfect fit in ...
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17 views

Can I set batch size to 1

I am trying to train a T5 (t5_large) transformer model on some data. Since it's out of cuda memory, I was forced to set ...
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1answer
32 views

Is it possible to train two neural networks combined with same output?

Say I have two kinds of input that I want my neural network to learn a possible from: one 2D image some 1D metadata about the image This case and similar cases seem problematic to me because the two ...
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2 views

How are t+n predictions generated?

I'm trying to understand how ARIMA and other models generate or produce a prediction sequence. I understand how they fit the model with each point with the training set, and then testing with the ...
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18 views

If I know specific pair of characters that model confuses in OCR task how can I fixe it?

I train OCR model to recognize cyrillic handwritten text. I know, for example, that it confuses very often 'Б' with '6'. How can I use this information to fine tune the model ? Just in case, my ...
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78 views

Machine Learning Classification of Changes in a Time Series

I would like to classify the changes in the time series depicted in the figure below—representing an angular position history of a robot about the vertical axis—into increment/decrement of roughly (...
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14 views

Percentage of positive target values in dataset and the train/test split

Suppose that in my dataset of 100 observations, only 25 have a target variable equal to 1, while the other 75 have target variables equal to 0. Should the portion of target values that are positive ...
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17 views

Reporting cross-validated score and test score

Is this the right way to do cross-validation and testing of a machine learning model: Split my data into train (85%) and test (15%) Do hyperparameter tuning based on the train set Do 10-fold cross-...
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1answer
14 views

Shall I present predictions on the (oversampled) training set as well?

I am dealing with an imbalanced classification problem and used oversampling on my training set to to predict on my testing set. My PI insists on presenting evaluation metrics of the different trained ...
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45 views

Interview question: train/test error and "best" model

I recently had a puzzling interview question and I am wondering whether anybody can tell me the intended answer. The question shows train and test error for three models plotted against the number of ...
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23 views

Two datasets have different imbalanced class. How to split?

I'm new in machine learning. Actually I have two datasets files as my scrapping results from different news webpages. I want to preprocess to just selecting relevant news. So I would like to perform ...
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1answer
524 views

How LightGBM deal with a new categorical value in the test set

Suppose I have the training data set $(X, y)$ where $X$ is my feature space $(x_1, \dots, x_n)$. Let $x_1$ be a categorical feature column. In my test set, if the feature $x_1$ takes a new categorical ...
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114 views

Train and test score - overfitting?

I have hourly time series data with a range of two years. I want to test my model when predicting my target variable (continuous) for a specific week. I'm doing the following: Splitting my data into ...
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4answers
645 views

Train and Validation vs. Train, Test, and Validation

I am embarking on a new job that will give me the opportunity to do some cool machine learning stuff. I haven't touched this stuff on a deeper level since graduate school and I wanted to get some ...
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9 views

How to evolve an already trained model with new data

How to evolve a model when new data come out? Suppose I have a model $M_1$ trained on data $D$. After the model $M_1$ is trained, new data $T$ is available. How to train a new model $M_2$ from $M_1$ ...
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1answer
269 views

Random Forest Regression and Overfitting

I did gridsearch with corss-validation on a trainingset to search for best hyperparameters for a Random Forest Regressor. And indeed the best parameterset gives good results in cross-validation (R^2 ~ ...
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50 views

How to compute TBATS forecast accuracy without specific test set?

I have used the TBATS model on my data and when I apply the forecast() function, it automatically forecasts two years in the future. I haven't specified any training set or testing set, so how do I ...
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1answer
34 views

Method for selecting training data and identify predictive genes in a survival model

I am performing a coxph survival analysis and want to split my data into a training and test set. During the training I would like to identify the "best" ...
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1answer
110 views

How is stratified sampling better than sampling equally from all classes while crossvalidating?

I can see that stratified sampling helps in maintaining the same class distribution in the training set as in the original dataset. However, my understanding is that ideally, the model should be ...
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2answers
43 views

Training a Neural Network on Music

I'm very picky about the music I like. I can't say I like a genre in particular because my tastes in music boil down to how a specific song sounds. For a while now, I've had a vision of creating a ...
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47 views

High precision, but low recall on training data. What could be wrong?

I am training RNN for timeseries binary classification. I observed that network has high precision, but low recall on both training and testing data. I tried multiple architectures, but same problem ...

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