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Questions tagged [training]

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5 views

BERT pretraining hardware information [on hold]

I want to pre train BERT with a dataset of legal documents. Can I do it on google colab with TPU runtime ?
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saving a model during training of an RL agent

I am training an RL agent using PPO2 algorithm. Iam using stable-baselines library. During the training process, my rewards are slowly increasing and stabilizing, but are falling down suddenly. I ...
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1answer
18 views

Target encoding before split on skewed data

Hi My data is distributed like follow: And I only have categorical variables on many many levels. As I need to make a regression task I thought about doing leave one out encoding on my categories. ...
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14 views

CNN models comparison

I coded a 38 layer CNN and 8 layer CNN but there's something wrong in my 38 layer CNN, which doesn't learn anything. Not able to fugure out what's wrong. They were trained on CIFAR.
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2answers
191 views

Training a model sample by sample

I'm training a Scikit model but it seems that in all examples, they call the fit method on the entire training set. What I want to do however is call it per sample (...
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4 views

Training Algorithm for pointcloud data (3d point data)

I have a "PointNet" neural network which theoretically can work with any number of points as input. I have trained the model using an equal number of points from each object. That is fairly simple and ...
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11 views

Accuracy to big when train yolov3

I am trainning yolov3. My result is not as my expected. I think accuracy must be less then 1.0 But I got accuracy and avg too large, in this case is 1577.76 average. Do I still working well?
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2answers
18 views

Suggestions on how to explain 'models' & 'algorithms'

I guess other members of this Stack have ran in to this before, but I may be wrong: Have you ever been approached and asked to explain the difference between models and algorithms? This happened to be ...
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11 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 ...
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9 views

What should be ideal ratio for number of unique target label vs number of training set samples

For a multiclass classification problem in Machine Learning, is there any rule for ratio of number of target class values vs number of training samples? For example, I have 2000 records to train on ...
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4 views

Is there any relation between binary/ternary quantization using in deep learning and fuzzy?

I am new with binary/ternary quantization but its structure seems to have some relation with fuzzy. Am I in right way? Is there any relation between binary/ternary quantization using in deep learning ...
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1answer
17 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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1answer
16 views

Transfer learning VGG16 does not work as expected. (Detect tacos as hamburgers)

I am new in this field of machine learning, to test I wanted to do a simple project. Create a cnn capable of recognizing hamburger images. As I do not have the ability to collect more than 10,000 ...
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2answers
32 views

Oversampling/Undersampling only train set only or both train and validation set

I am working on a dataset with class imbalance problem. Now, I know one needs to oversample or undersample only the train set and not the test set. But my issue is: whether to oversample the train set ...
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21 views

How do I compare more than 20 deep learning models?

I have to compare several deep learning models (CNNs) based on the same dataset. For estimating the model skill's I use the train_test_split instead of ...
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1answer
65 views

clarification on train, test and val and how to use/implement it

So far I think I understood the differences between the training, test and validation set. Basically it is like in this image: Training set: The data where the model is trained on Validation set: ...
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1answer
17 views

How to construct validation set for time series for NN?

I would like to train my model with a validation set. As the data is a time series I have to use timeseriessplit: ...
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0answers
18 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 ...
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7 views

Training data for Tesseract

I have to train my tesseract to detect different variations of a letter for example, u,û,ü,ù should all mean u. Is this possible and if yes how should I train it and how should the dataset be made ...
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22 views

Issues with Implementation of CNN based on Paper

I am attempting to duplicate a CNN in a paper, and am having issues with bad accuracy and loss not decreasing past 40. As described in this paper, specifically on pages 6/7, the network architecture ...
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18 views

How to avoid different accuracies when training with subsets?

when trying to train a CNN with randomly selected small subsets (each same size) of the training data set, I get different results in accuracy (the accuracy varies from 0.75 to 0.85). I determine the ...
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2answers
67 views

Why can we not split train test data with 0.01 as parameter or 99% training data

Most of the blogs mention about a good thumb rule to be 80-20 split for the train and test respectively. My special case is a time series dataset and it is for the stock prices, which IMO is very ...
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2answers
31 views

How to deal with a feature that has lot of categorical values?

I know this question has been asked before and I have tried a few things but those things are not working as expected for my usecase. I have a 500 length feature vector. One of these features is a ...
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20 views

Beating Roulette with Neural Networks, YoloV3, and PyTorch

Background: I am in my last semester of electrical engineering, and I am working on my senior design project. The senior design project is a two-semester design project in which students outline, or ...
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1answer
26 views

Accuracy noise patterns during model training

I'm training a logistic regression model on a small dataset. I have about 1300 samples that I split into a training and a testing set (70% and 30% respectively). The training seems ok, however when I ...
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38 views

Data leak when training on future data and testing on present [closed]

Given a time series dataset. Using simple train_test_split, then reversing the train to test and test to train i.e. using the future data to train and present data to test, where does one induce leak ...
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2answers
106 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 ...
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1answer
49 views

Given a machine learning algorithm, what is the minimum size of the training set for it?

I understand that the more data we have, the more reliable is our model trained on that data. I also understand that the more parameters a machine learning model has, the more training data it ...
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9 views

Shrink the training set during the learning process

Is there any way to change the size of the training set during the learning process? For example, let's say we have four classes (with their distribution): [A (90%), B (5%), C(2%), D(3%)]. Can we ...
0
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1answer
104 views

LSTM loss function and backpropagation

I'm trying to understand the connection between loss function and backpropagation. From what I understood until now, backpropagation is used to get and update matrices and bias used in forward ...
1
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1answer
170 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 ...
0
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1answer
61 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 ...
2
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1answer
79 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 ...
0
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1answer
39 views

How to deal with a constant value as an output from neural network?

I am using feedforward neural network for regression and what I get as a result of prediction is a constant value visible on the graph below: Data I use are typical standardised tabular numbers. The ...
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1answer
29 views

On design of the training set: conceptual question

I am curious to know how training data should be constructed so that it scales to examples that are not a part of the training data. For example, the problem that I am facing right now is in the ...
2
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2answers
61 views

Resampling for imbalaced datasets: should testing set also be resampled?

Apologies for what is probably a basic question but I have not been able to find a definitive answer either in the literature or in the Internet. When dealing with an imbalanced dataset one possible ...
0
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1answer
18 views

Should inputs be shuffled for training a model with expected time dependency?

Consider a prediction model with numerical inputs and outputs. Suppose data is inserted tick by tick, i.e., when new data is available it is inserted asynchronously. Current output depends on current ...
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14 views

SRCNN - the colors disappear from the output

I'm training a custom CNN (built for academic purpose) to perform Super-Resolution. I based my work on this review. The input of the network is a RGB color image, so 3 channels of size image_width x ...
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2answers
74 views

Splitting training and test set with financial data

I am using trees algorithms (decision tree, random forest and XGBoost) to forecast the sign of the returns in the stock market (classification). I am using this article as a reference: http://...
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1answer
127 views

DC GAN with Batch Normalization not working

I'm trying to implement DC GAN as they have described in the paper. Specifically, they mention the below points Use strided convolutions instead of pooling or upsampling layers. Use only one fully ...
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2answers
67 views

Which service could I use to train my networks?

My laptop's Intel i7 3630QM 2.4GHZ, 8Gb RAM and GXForce 670M are clearly not sufficient... By reading some papers, I've written an SRGAN with Python Keras. At runtime there is no error but training ...
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2answers
27 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. ...
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22 views

Architecture choice for variable input dimension sizes

So, I am doing this project where I have lets say a bunch of points. Each of those points can have a different number of RGB values. So lets say point 1 might have 30 RGB values, point 2 might have ...
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0answers
35 views

LSTM validation loss not improving

I'm a noob in the ML world and am currently building an LSTM to forecast the next page a user is going to visit on a website. My dataset is pretty much a mapping (with sliding window) from one page to ...
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0answers
27 views

Neural Network to generate data for another network?

I was wondering if its possible to develop and train a neural network that generates training data for another network (or possibly itself). I came to this thought wondering the difficulty in creating ...
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0answers
25 views

How strong is the generalization ability of YOLO?

I have a question about the generalization ability of YOLO or deep learning methods in general: I am working on vehicle detection and classification in highway traffic surveillance videos. As you ...
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1answer
13 views

Is it okay to use training data for validifying the trained model?

Currently, I have trained my model through 5-fold cross validation with very small amount of the sample (n=240). I used whole data set to train and got quite low performance in terms of accuracy, ...
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2answers
673 views

In the context of Deep Learning, what is training warmup steps

I found this term "training warmup steps" in some of the papers, what exactly does this term mean? Has it got anything to do with "learning rate"? If so, how does it affect?
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1answer
61 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 ...
2
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2answers
71 views

Is it correct to join training and validation set before inferring on test-set?

I would like to know if is a correct procedure to join training-set and validation-set together, in order to train the model on ...