Questions tagged [training]

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203 views

How many epochs to run during hyperparameter search?

If I'm doing a hyperparameter search and comparing two different hyperparameters (but not number of epochs), is there some established rule of thumb for how many epochs to run? If I just compare ...
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36 views

NN training with repetitive features

I posted the question also on ai.stackexchange but it didn't get any answers so I though I could try here. Here is a copy paste: Let's say you are training a NN in a RL setting where the state (i.e. ...
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34 views

A Deep CNN model delivering better results with standardization, when compared with normalization

I developed a deep CNN model, based on the architecture discussed in this paper, to generate predictions for time series data. My training data is shown in the figure below: In order to train the ...
3
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1answer
40 views

Validation data shall be in broken down into batches or not?

I am using fit_generator to train the model. The training dataset is being read from a generator function which gives data in a constant batch size. Now I want to ...
3
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0answers
158 views

Training deep CNN with noisy dataset

I am training a Mask RCNN model with a train dataset that has been generated from some simple computer vision operations (color thresholding) and some morphological filtering. The train set captures ...
3
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0answers
199 views

How much text is enough to train a good embedding model?

I need to train a word2vec embedding model on Wikipedia articles using Gensim. Eventually, I will use the entire Wikipedia for that but for the moment, I'm doing some experimentation/optimization to ...
3
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0answers
264 views

How to add a new label to a multi-label dataset (like Open Images)

Given N classes in a multi-label dataset and a trained classifier C, how would we add a new class N+1 to the dataset, and fine-tune the trained classifier C such that it now predicts N+1 labels? (lets ...
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0answers
14 views

What is the appropriate approach for training time series data against multiple, consecutive labels?

Let's say we have a time series $\{{\bf x}_i\}$ of features and are trying to learn to predict a time series $\{t_i\}$ using a neural network. Our goal is to be able to predict the time series value $...
2
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0answers
19 views

Training pipelines where featurization/NLP is more expensive than backprop

I'm working on a document classification project and I'm using a neural net in tensorflow, where the features are 300-dimensional word embeddings, either from fastext or word2vec (yes I know that ...
2
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2answers
1k views

What can be the cause of a sudden explosion in the loss when training a CNN (Deeplab)

I am training the following deeplab CNN: https://github.com/tensorflow/models/tree/master/research/deeplab During training I see the following loss: The first 50k steps of the training the loss is ...
2
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1answer
267 views

how is correct usage of the validation split in neural networks?

I have a dataset separated in train, test and validation splits. After each epoch, I evaluate the loss and accuracy in the validation split. When the loss in validation split is not better, I stop ...
2
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2answers
37 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. ...
2
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1answer
59 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 ...
2
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0answers
55 views

Replacing mean by median over batch-size to lessen the impact of outliers

In the case of training a Neural Network on a regression task. Assuming the data has a significant amount of outliers. Provided that the error needs to be RMS and not MAE. Can it be better (as in less ...
2
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0answers
54 views

Performance diagnostics in mxnet gluon (e.g. plotting training vs validation loss over time)?

Tensorflow has tensorboard, is there any recommended way to plot classification error/loss over time in mxnet?
2
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1answer
577 views

Why is performance worse when my time-series data is not shuffled prior to a train/test split vs. when it is shuffled prior to the split?

We are running RandomForest model on a time-series data. The model is run in real time and is refit every time a new row is added. Since it is a timeseries data, we set shuffle to false while ...
2
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0answers
29 views

Correct approach to usage of class labels in cell imaging data

As part of a group project at university, we are given a series of videos of cell cultures over a 24 hour period. A number of these cells (the "knockout" cells) have had a particular gene removed, ...
2
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0answers
598 views

How to train the generator in a recurrent GAN (Keras)

I am trying to train a Recurrent GAN that is meant to generate geospatial movement data (sequences of 3-tuples of latitude, longitude and time). You may simply consider it a sequences of vectors with ...
2
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0answers
144 views

How to resolve the instability of average reward per episode in training of DQN (Deep Q-Network)?

what is shown when average reward per episode in training is unstable? If there is big difference between average reward per episode and final reward by test section, what we can say? For instance in ...
2
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0answers
24 views

Force Neural Net to attempt to predict every class

I am training a (deep) neural net to classify approximately 60 different classes. The range of occurrences of each class in the dataset is wide, 3 orders of magnitude from the most represented to the ...
2
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0answers
385 views

Matlab: setting static iterations per epoch in a CNN

I'm building a convolutional neural network using Matlab's neural network toolbox. I have code designed to cross-train the network with different data sets, using the previous network's layers in ...
2
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0answers
878 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 ...
2
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0answers
36 views

Term for Methods of Representing Repeated Text in Classifier

A colleague told me that there are terms for two different methods of representing repeated text in the training set for a classifier, but he could not recall them. What are the terms for the options ...
2
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1answer
151 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 ...
2
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0answers
135 views

Multiple models vs. Single model for prediction

I am using the Darknet Convolutional Neural Networks to detect people (as in, humans) and furniture in a single image. If I train the model twice, one for people, one for furniture. I seem to get ...
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10 views

What's the best way to train a model when having a very big dataset split in batches?

I was wondering what is the best way to train my Keras Model, in a binary classification context. My full dataset is composed of 2.3M rows and 120 columns, which is really big. As you would imagine, ...
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1answer
24 views

Label A records B times or label A*B records

This question concerns pre-training data sourcing. Suppose you have a human workforce of B individuals and a potentially unlimited source of data. The task is ...
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0answers
12 views

Defining objects in training data for deep learning

I am performing end-to-end deep learning in ArcGIS Pro 2.5, following a similar procedure to the one set out in this tutorial: https://learn.arcgis.com/en/projects/use-deep-learning-to-assess-palm-...
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0answers
11 views

Solving Feature Distribution variance between Training and Prediction for Ranking models

I am building a linear regression model to improve ranking of documents. And trying to identify problems due to which model performance estimates don't match actual impact One major problem is ...
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1answer
14 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,...
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28 views

Is the “training loop” used in AlphaGo Zero the same as an “epoch”?

I am confused about the training stage of AlphaGo Zero using the data collected from the selfplay stage. According to an AlphaGo Zero Cheat Sheet I found, the training routine is: Loop from 1 to 1,...
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1answer
117 views

ValueError trying to use a pickled scikit-learn model

I am new to data science and trying to learn something. I was able to complete the prediction with 98% accuracy and i saved it as pickle model. Now while trying to predict using this model I am ...
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0answers
16 views

How many augmentated data points for each training image?

What are some useful rules of thumb for picking the number of augmenters per training image? I realize this is a hyperparameter I can vary and test: I'm just trying to get a sense for reasonable ...
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0answers
18 views

Vector Autoregression forecasting with large dataset

I am trying to use VAR to forecast electricity price for a whole day and I have a dataset with over 20000 observations (price for every hour) from 2015-2017. My first intuition was to select 19975 ...
1
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1answer
369 views

Error: An operation has `None` for gradient with categorical_crossentropy

I am trying to train my discriminator network using Keras with TensorFlow backend. The network is meant to classify the input into one of the 9 output labels. I am passing a 2D input (height, width, ...
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0answers
91 views

Grape disease detection

i'm trying to realize a detector for diseased grape leaves, for this par of the project i'm just interested in detecting lets say, the percentage of diseased to healty leaves and/or place a flag where ...
1
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1answer
44 views

How to deal with annotation errors?

I know my annotators are not perfect, sometimes making mistakes. What would be the best way to deal with the annotation errors for my training data? Thanks!
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0answers
20 views

How to teach algorithm to mimic paths in a certain enviroment

I have a set of scenarios which represent the movement of a car in a certain environment containing some obstacles. So for each scenario I have the position of the car (x,y,t) and a description of the ...
1
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1answer
678 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 ...
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1answer
173 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 ...
1
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1answer
104 views

How interpret keras training loss without compare with validation loss?

I have several implementation of the same neural network, but each one with different starting parameter. This is one of my plot comparing the training loss of the base experiment with the training ...
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1answer
106 views

Training data : forecasted or actual?

I am working on a time series prediction problem. I am using keras models for machine learning. For this prediction, weather variables are used as input. They can be of two types: forecasted and ...
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0answers
65 views

Should images with multiple objects of the same class be used as training sample for multi-classes object detection models?

Let's say the model try to detect all the grapes on a branch of grapes. Can I use images of a grape branch with all the grapes labeled as a training sample? Will it affect the quality of the RPN ? Is ...
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1answer
303 views

Accuracy and Loss in MLP

I am trying to explore models for predicting whether the 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 ...
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0answers
26 views

Unexpected shape of “training curves” in NN

I'm trying to find the best configuration for my NN (in terms of batch size, learning rate etc) and noticed the following unexpected behavior. The AUC scores, computed on validation data, as ...
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0answers
31 views

Strangeness in validation loss between CPU vs GPU when training CNN

I've been training an implementation of Mask R-CNN and it was training very successfully on my CPU but I've just set up my GPU and it is giving some strange results when looking at my validation loss. ...
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0answers
577 views

Time series regression using SVR

I have time series data stored in a data frame as follows: Time, c1, c2, c3 0, 0.55, 0.4 , 0.3 1, 0.8 , 0.1 , 0.6 2, 0.9 , 0.5 , 0.7 .... And I want to ...
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0answers
26 views

Dynamic window regression model

I have a signal and want to predict y which present Number of requests, using regression models. Currently, I am using OLS regression model to predict y. But the prediction error is very high, as my ...
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1answer
43 views

Tool for test/train automation

I need to test different datasets as well as different algorithm implementations. The current workflow looks like: Perform feature extraction from train set Train classifier on this features Feed ...
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0answers
83 views

Add training data to YOLO post-training

I've been playing around with YOLOv3 and obtaining some good results on the ~20 custom classes I trained. However, one or two classes look like they can use some additional training data (not a lot, ...