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Questions tagged [training]

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21 views

How to train non image data in batches from disk?

I am working on a project where I have 50 .npy files with each of shape (77156, 30, 50, 1) representing ...
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1answer
18 views

Change rate of cross validation data, after training

Say we have N of labeled data, and we need to take some part for the cross validation (we will skip test part for this case). We ...
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0answers
107 views

FaceNet training, tripletloss not decrease but accuracy increase then stuck,what are possible causes?

as you can see,triplet loss(pink curve in the left) do not change,but accuracy increase then stuck,what are possible reasons?
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1answer
508 views

Issues with training SSD on own dataset

I'm new to ML and trying to train a SSD300, with some Keras-Code github.com/pierluigiferrari/ssd_keras I found on github. For training I'm using an own (very small) dataset of objects that are not in ...
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1answer
48 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 ...
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0answers
34 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?
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1answer
68 views

Is splitting the data set into train and validation applicable in unsupervised learning?

I am having a tough time implementing all the steps of setting up support vector machine (SVM) for unsupervised learning. My data set is labelled but for educational purposes I am learning ...
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1answer
72 views

Suggestions for labeling data for named entity recognition [closed]

Is it good to label the data based on sub category than parent category? For example: for drugs data ... label the drugs dose as drug_dose or label the drug dose as different type of dose like ...
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2answers
70 views

Is it ok to train the model only on the interested part of the data?

Let's say I have a dataset where one feature is 'Car type' : say 'A', 'B' and 'C'. The test set consists of samples where 'Car type' is always equal to 'A'. Therefore, should I train my model only on ...
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147 views

Validation curve

I'm learning about data science and I've been checking several tutorials. Now I'm trying some validation curves on the problem sample I'm resolving and I'm having some troubles with it. This is the ...
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0answers
124 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 ...
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4answers
126 views

Weights not converging while cost function has converged in neural networks

My cost/loss function drops drastically and approaches 0, which looks a sign of convergence. But the weights are still changing in a visible way, a lot faster than the cost function. Should I ensure ...
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3answers
84 views

weight training speed too slow in CNNs

I'm writing my own CNN code from scratch. Though I got fast, converged and satisfactory results, the trained weights change very little in value (while cost/loss function drops in time rapidly in a ...
2
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1answer
348 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 ...
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1answer
43 views

Computing number of batches in one epoch

I have been reading through Stanford's code examples for their Deep Learning course, and I see that they have computed ...
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0answers
23 views

How to train LSTM with previous cell's prediction as an input in Keras?

At the moment I'm using a simple Keras model to learn a sequence of items and after it using the trained model to generate new sequences . I want to change the training to be in the same manner as ...
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1answer
96 views

Unsupervised Learning and Training Data

As far as I know, we need to use training data to find out the relation between the features, also known as input values, and labels, that are output values, in supervised learning. After that, by ...
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0answers
40 views

Train and Test Error dependence on size of data

I was reading about Adaboost Alogorithm and learned that if initially we split the dataset equally for training and testing, apply the algorithm. And then gradually start increasing the size of train ...
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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, ...
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1answer
57 views
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25 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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1answer
222 views

Why do most GAN (Generative Adversarial Network) implementations have symmetric discriminator and generator architectures?

For example, if the discriminator is a vanilla network of n layers, each with n(i) units, then, typically, the generator will also be a vanilla network of n layers, each with n(n-i) units (except the ...
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2answers
109 views

Face Recognition (Scalability Issue)

Background I would like to build a face recognition model for registration and login for some kind of service. For example, using this approach (CNN + SVM). When a new user wants to register a ...
2
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1answer
465 views

Training a convolutional neural network for image denoising in Matlab

I am currently trying to train CNNs to remove Poisson noise from images. The software I am using is Matlab 2018b, however the results I am getting are poor. I have followed the steps provided in the ...
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18 views

I have created a model that classification sentences. How do I create a good dataset when I train this model further?

I used bidirectional lstm I have a model that classification as spam and general trained with about 130,000 data. The model has 90% accuracy for sentences over a certain length, but 75% accuracy for ...
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140 views

How to cross validate a DNN model?

You have a binary classification model giving a decent score on selected metrics. The model has been trained using early stopping. The epoch with the lowest loss is kept. Now you want to cross ...
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1answer
61 views

Confusion on Delta Rule and Error

I'm currently reading Mitchell's book for Machine Learning, and he just started gradient descent. There's one part that's really confusing me. At one point, he gives this equation for the error of a ...
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2answers
188 views

Normalization before or after resizing

I'm training deep learning network using images (to be exact - I'm solving semantic segmentation problem). What's the proper order of resizing (I need to resize images to fixed width X height) and ...
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0answers
6 views

effects of number of running time periods on examining the DQN quality?

What are the effects of the number of running time periods on examining the DQN quality? I mean "T": time periods of training and testing. If there is not an obligation to set it to a value in the ...
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0answers
21 views

How apply Reinforcement Learning in the following case?

Suppose that I have to move from point A to B and I have to choose among 3 different paths. But we don't know the traffic in each path, so what is the training rule to use to learn the best behaviour? ...
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0answers
215 views

“10-year-challenge” data for age algorithms? [closed]

Both on FB and IG, I see people posting themselves before 10y and now. I have no idea how this challenge started. Could it be a way to collect a colossal amount of data, that could be used to train ...
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1answer
48 views

Difference in labelling and normalizing train/test data

I am working on a dataset comprised of almost 17000 data points. Since it's a financial dataset and the components are many different companies, I need necessarily to split it by date. Therefore, ...
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3answers
462 views

Is it possible to make a CS:GO Machine Learning AI? [closed]

I am not an expert on Machine Learning, Neural Networks or NEAT. In fact, I probably have no clue what I'm talking about. My question is if you can make a learning AI that learns to play complex ...
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0answers
54 views

Semantic segmentation training on images of different sizes - good practices

What are the good practices of handling images when training the neural networks for semantic segmentation, but the images have different sizes and aspect ratios? Also, how to properly handle small ...
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0answers
22 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. ...
2
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0answers
433 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 ...
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1answer
91 views

Conjugated gradient method. What is an A-matrix in case of neural networks

I am reading about conjugated gradient methods to understand how they exactly work. I understand that a pair of vector $u$ and $v$ are conjugated with respect to $A$ if $u^TAv=0$. I also read that $A$ ...
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4answers
190 views

Neural Network unseen data performance

I started dabbling in neural networks quite recently and encountered a situation which is quite strange (at least with my limited knowledge). The problem I'm using a NN is a regression problem which ...
2
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2answers
986 views

What's the advantage of multi-gpu training in real?

The decreasing speed of training loss is almost the same between one gpu and multi-gpu. After averaging the gradients, the only benefit from multi-gpu is that the model seems to see more data in the ...
2
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1answer
69 views

Sequential Modelling: Multiple Sequence to One or Sequence to Sequence

Suppose I have a single sequence of $x_1, x_2, ..., x_n$ and corresponding labels $y_1, y_2, ..., y_n$. An example would be a person makes website visits $x_i$ and the label $y_i$ tells us if there ...
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1answer
60 views

Can accuracy become worse on the training set with more epochs?

I know that overfitting occurs when the accuracy on the training set improves but the accuracy on the validation set decrease. So, we must stop the training. I would like to know if this is a rule ...
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2answers
190 views

Validation accuracy is always close to training accuracy

I am trying to tune the hyperparameters of a LSTM I have to do time series forecasting. I have noticed that my validation accuracy is always very close to my training accuracy. I am not sure whether ...
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1answer
277 views

How to avoid covariate shift in python and distribute classes in each train and test phase?

We all know that with the use of sklearn package from python, we can create X_train, X_test, y_train and y_test via this code: ...
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3answers
95 views

Can you learn an algorithm from a trained model?

Are there any papers where an algorithm was entirely based on the results of a trained model? Let me explain. Suppose you want to come up with an algorithm that sorts three numbers $a,b,c$. I can ...
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1answer
977 views

Caret + RStudio: Error “Please make sure `y` is a factor or numeric value” when training

I'm new to Caret and I've been trying a couple things to get the hang of things. But this error happened to me and I'm not sure why. I've been trying to train a model with some data I got from "...
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0answers
433 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
85 views

Free Service for Alpha Zero training

I'm an AI student I need to train a deep neural network using the Alpha Zero (Silver et al) for a simple game using this implementation: http://web.stanford.edu/~surag/posts/alphazero.html. I was ...
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3answers
597 views

Downsampling and class ratios

My target variable is whether an application is accepted or not. It is a highly imbalanced target with 98.5% of applications accepted. I am unclear about the concept of downsampling. If I were to ...
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2answers
889 views

Both train and test error are decreasing in XGBoost iterations

I have an issue with training an XGBoost classifier in a sence that both train and test error only decrease throughout more iterations (num_boost_round) even if I use 1000 num boost rounds and 10 ...