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.
680
questions
0
votes
0
answers
13
views
How can I tell if my CNN tuning made a difference?
I'm working on a detection CNN, estimates pose for some classes of objects. I am able to compute a bunch of different metrics on performance, things like position error, rotation error, tracking ...
- 101
0
votes
2
answers
721
views
Why is my DCGAN not converging?
I'm training a tf DCGAN on the MVTec hazelnut dataset and I found some difficulties. The problem is that after a lot of epochs the generate does not produce some quality images.
My model is the ...
CommunityBot
- 1
0
votes
0
answers
18
views
Training with few samples, dropping training loss but constant validation loss
I am training a resnet50-based model using transfer learning. My dataset has 10 classes and about 10 occurrences per class, so it is very small. The training loss is decreasing steadily to 0.07 for ...
1
vote
2
answers
84
views
Will my validation loss eventually go down?
I'm currently training a binary classifier that takes in 2 inputs, and outputs which object it thinks is "better."
I have an absolutely massive dataset, about 2 trillion records, and I'm ...
CommunityBot
- 1
2
votes
3
answers
93
views
How to use External Data Sets in test set
I have a doubt regarding usage of external datasets like gdp rate, unemployment rate... etc., in test set for time series prediction. These datasets are historical and can be used along with train set,...
- 71
3
votes
2
answers
610
views
Confusion over training accuracy vs. training loss
I had a small discussion with my friends on overfitting and we became confused over the two terms: "training accuracy" and "training loss (or cost)". This is the first time I've ...
- 537
0
votes
1
answer
1k
views
KL divergence loss first decreases and then increases in VAE training
I am training a VAE on CelebA HQ (resized to 256x256). The training is going well, the reconstruction loss is decreasing and reconstructions are also meaningful. But, the problem is with KL divergence ...
CommunityBot
- 1
5
votes
2
answers
4k
views
Batching in Recurrent Neural Networks (RNNs) when there is only a single instance per time step?
I have scoured the internet and books, but everything seems to use num_steps and batch_size or similar terms interchangeably and ...
- 1
0
votes
1
answer
16
views
Holding batch size constant, will a bigger dataset consume more GPU memory?
If you hold (mini) batch size constant (as well as everything else) but increase the number of examples (and therefore the number of training iterations), should you expect a (significant) increase in ...
- 101
1
vote
1
answer
357
views
Is "adding the predictions to the real data for new training and prediction" a good idea for LSTM?
Considering we have trained our model with a lot of data for "many-to-one" prediction. Then we like to forecast the future data of next 10 days. So we use last 60 of existent data and predict the ...
CommunityBot
- 1
1
vote
1
answer
232
views
Average loss is 0 when training dataset with darknet yolov4
I am currently training a dataset using yolov4 darknet from AlexeyAB Github found here:
https://github.com/AlexeyAB/darknet
The dataset I am training is called FishNet Open Images. The dataset has 86,...
CommunityBot
- 1
0
votes
1
answer
170
views
How to prepare training data for deep learning models
I am working on a project which involves the application of deep learning models. I have collected training data. In collected images, I have more than one object in interest. I am not very clear how ...
CommunityBot
- 1
10
votes
3
answers
28k
views
How to split train/test datasets having equal classes proportion
I would like to know how I can split in an equal number the following
Target
0 1586
1 318
in order to have the same proportion of 0 and 1 classes in a ...
- 6,082
2
votes
1
answer
435
views
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 ...
CommunityBot
- 1
1
vote
1
answer
63
views
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 ...
CommunityBot
- 1
0
votes
1
answer
48
views
1
vote
1
answer
586
views
How to split a dataset into train and test sets for time series (multiple step-multiple output forecasting)?
I am trying to use an LSTM neural net to do multiple step / multiple output forecasting (I predict multiple values in one time knowing some values in the past). But, I have realized that I must be ...
CommunityBot
- 1
0
votes
1
answer
1k
views
ValueError: Layer model expects 2 input(s), but it received 3 input tensors using generator
I am trying to fit a model using generator function and I get the following error:
...
CommunityBot
- 1
2
votes
1
answer
1k
views
How to impute using simple imputer (custom function)
I am imputing my data using simple imputer from sklearn. i want to test many different ways of applying transformations to the data. i.e for logisitcic regression i would like to
remove nans and ...
CommunityBot
- 1
2
votes
1
answer
100
views
Training a model where each response in the observation data has a different known varience
I have a dataset where each response variable is the number of successes of N Bernoulli trials with N and p (the probability of success) being different for each observation. The goal is to train a ...
CommunityBot
- 1
0
votes
0
answers
31
views
How was the word2vec model trained?
Let's take the CBOW (continuous bag of words) model as the example.
Suppose that, there are $c$ context words, each of which is a one-hot encoding vector. So the total number of elements of input ...
- 46
0
votes
1
answer
42
views
PyTorch ResNet implementation's Training Loss increasing with every Epochs
I'm implementing a ResNet network from scratch using PyTorch. This network is unique to my requirements, since I need to perform Image Classification for Satellite Imagery with 14 different channels ...
1
vote
1
answer
359
views
Bertopic with embedding: unable to use find_topic
I've used BERTopic with success for the following tasks: get topics, visualise (topics, barcharts, documents ...) and DTM (extended to get area plot with considerable success).
However, I am unable to ...
CommunityBot
- 1
1
vote
2
answers
758
views
Using GPUs of other machines in the network with Keras
My situation is as follows:
I have a rather cheap laptop with Ubuntu 18.04 running on it that unfortunately is not powerful enough (old, cheap GPU) to train deep learning models with. I am located in ...
- 1
0
votes
1
answer
42
views
Very basic but how to understand data statistically for machine learning?
I’m trying to solidify my statistics so I really know how to use them in my analysis/models. However my concept of statistical testing gets completely messed up by context. I’m unsure defining exactly ...
- 36
3
votes
1
answer
2k
views
Training an ensemble of small neural networks efficiently in TensorFlow 2
I have a bunch of small neural networks (say, 5 to 50 feed-forward neural networks with only two hidden layers with 10-100 neurons each), which differ only in the weight initialization. I want to ...
CommunityBot
- 1
0
votes
1
answer
283
views
What causes explosion in MSE when training?
I (probably) well overfitted/overtrained a model. But I was just curious as to what might cause this type of behaviour. I carried on training (Epoch 1/50 is not the first epoch of training this model)....
CommunityBot
- 1
0
votes
0
answers
9
views
How do we modify the early stopping procedure to account for better losses after initial rise in losses?
I have a question regarding the usage of early stopping in the training of my forecasting model. Curious about how the training would go without early stopping, I observed that the test loss seems to ...
1
vote
2
answers
624
views
Train a spaCy model for semantic similarity
I'm attempting to train a spaCy model for the purposes of computing semantic similarity but I'm not getting the results I would anticipate.
I have created two text files that contain many sentences ...
CommunityBot
- 1
1
vote
1
answer
203
views
Is it possible to update data and retrain just one of several data series in bigquery model
I am building something very similar to this BigQuery ML example project.
My system is different in two ways:
Firstly it will need several thousand time-series so I would prefer to use the multiple-...
CommunityBot
- 1
0
votes
1
answer
40
views
Workflow when making a machine learning model
I'm new to data science, and kinda confused with the workflow and steps to make a model. Before learning the math and concepts behind the algorithms like SVM, linear regressions, etc, I would just ...
0
votes
1
answer
280
views
What the difference between a flattening validation curve and one that increases again?
I know that we monitor the validation loss to investigate overfitting. I am familiar with the validation curve that first decreases and then increases again. The increasing part means the model starts ...
CommunityBot
- 1
1
vote
2
answers
2k
views
How to train-test split a timeseries?
I have a dataset consisting of multiple timeseries for multiple users. So per user I have multiple timesteps, a value to predict per timestep and a list of features per timestep. I am currently ...
CommunityBot
- 1
2
votes
3
answers
90
views
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 ...
CommunityBot
- 1
0
votes
1
answer
64
views
Lower Variance vs. Higher Validation Scores
So I'm trying to compare between two models, say model(1) has training accuracy of 90% and validation accuracy of 86%, while model(2) has training accuracy of 87% and validation accuracy of 85%.
Now, ...
CommunityBot
- 1
1
vote
1
answer
196
views
How to calculate the training accuracy of a decision tree?
The hint given was to construct a confusion matrix.
- 1,352
3
votes
1
answer
67
views
How can I train a model to modify a vector by rewarding the model based on the modified vectors nearest neighbors?
I am experimenting with a document retrieval system in which I have documents represented as vectors. When queries come in, they are turned to vectors by the same method as used for the documents. The ...
CommunityBot
- 1
2
votes
2
answers
94
views
How to gather training data for simple voice commands?
I'm trying to build a machine learning model for recognizing simple voice commands like up, down, left, etc.
On similar problems based on images, I'd just take the picture and assign a label to it.
...
CommunityBot
- 1
0
votes
2
answers
88
views
Is it reasonable to do train/test splitting based upon information/entropy?
I want to divide my time series dataset into training and test sets. The data is seasonal and very noisy. When I randomly split, the test and train samples do not resemble in their ...
CommunityBot
- 1
4
votes
3
answers
104
views
Understanding Weighted learning in Ensemble Classifiers
I'm currently studying Boosting techniques in Machine Learning and I happened to understand that in Algorithms like Adaboost, each of the training samples is given a weight depending on whether it was ...
CommunityBot
- 1
2
votes
5
answers
9k
views
The model performance vary between different train-test split?
I fit my dataset to the random forest classifier and found that the model performance would vary among different sets of train and test data split. As what I have observed, it would jump from 0.67 to ...
0
votes
1
answer
1k
views
splitting into train test by train_test_split of float values?
How to split into train test by train_test_split of float values ?
I used LabelEncoder but I have about 300K lines and when I used the cross_val I saw ...
CommunityBot
- 1
0
votes
1
answer
1k
views
Why does Light GBM model produce different results while testing?
Using the Light GBM regressor, I have trained my data and, using Grid Search, I got the best parameters, but while testing with the best parameters I am getting different results each time, which ...
CommunityBot
- 1
2
votes
1
answer
2k
views
Backpropagation with step or threshold activation function
I understand that gradient descent is local and it deals only with the inputs to the neuron, what it outputs and what it should output. In all I've seen, gradient descent needs the activation function ...
CommunityBot
- 1
1
vote
2
answers
96
views
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 ...
CommunityBot
- 1
2
votes
2
answers
100
views
Does it makes sense to train the model on whole data?
Suppose I am training an lstm model on a stock price data.
So for first iteration say I have trained it on 80% of data and then tested it on rest of the 20% data and got the rmse value.
Now after this ...
CommunityBot
- 1
0
votes
1
answer
147
views
Train and Validation Curve
I'm new in DeepLearning. I'm not good at understanding and commenting on graphics.Can you help me with these graphs
CommunityBot
- 1
1
vote
1
answer
2k
views
Error: An operation has `None` for gradient with categorical_crossentropy
I am trying to train my discriminator network using Keras with the TensorFlow backend.
The network is meant to classify the input into one of the 9 output labels. I am passing a 2D input (height, ...
CommunityBot
- 1
1
vote
1
answer
745
views
Accuracy and Loss in MLP
I am trying to explore models for predicting whether a team will win or lose based on features about the team and their opponent. My training data is 15k samples with 760 numerical features. Each ...
CommunityBot
- 1
2
votes
2
answers
1k
views
Ideal difference in the training accuracy and testing accuracy
In a data classification problem (with supervised learning), what should be the ideal difference in the training set accuracy and testing set accuracy? What should be the ideal range? Is a difference ...
CommunityBot
- 1