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Questions tagged [training]

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2
votes
1answer
57 views

Basic classification question

I am wondering how I can manage a test data after using PCA or normalization and another thing like that in the classification because our model works on the representation given by its input vectors. ...
0
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1answer
463 views

What if my validation set is worse than my training?

I am running a CNN, on the 1st epoch my training set accuracy is 15% and validation set is 12%, by the 51st epoch my training accuracy is 87% and validation set is 13%. What is happening? What does it ...
0
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1answer
1k views

Error in training a merged model in Keras

I attempted to merge a VGG-16 and ResNet-50 model in Keras to benefit from the combined feature representations toward a binary classification task. I was successful in building and saving the merged ...
3
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1answer
583 views

“other” class in Image classification

In the MNIST dataset, you have 10 defined classes, one for each digit. But you don't have a "not a digit" class. It seems that most image classification datasets are the same. But in a business ...
1
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1answer
80 views

Any difference between adding epochs and duplicating data for neural nets?

Let's say I am training a neural net (e.g. convolutional network or LSTM). Generally, the longer the training (more epochs) leads to better accuracy, albeit at times at the expense of overfitting. ...
0
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1answer
81 views

How do machine learning models (e.g. neural networks) get better over time from new data?

I'm a complete newbie to the world of machine learning, and I'm currently working on implementing a model that will need to incorporate feedback, as well as changes to the data set (both feature & ...
0
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1answer
675 views

Validation accuracy for neural network

When training a neural network, I usually plot the accuracy obtained on the validation data (validation accuracy) as an intermediate measure of the network's performance – the final measure being test ...
2
votes
1answer
45 views

Including biased data in training model

My friend is in the business of getting cats to the top of mountains. He currently uses a set of heuristics to decide which cats are most likely to get to the top. For the ones he likes, he feeds, ...
1
vote
1answer
220 views

The sum of probabilities is more than 1

I have CNN architecture for object detection ( one object in image ) in KERAS. It has 22 Convolutional layers ( layer includes max pool , LeakyRelu and Batchnorm ) The last layes are following ...
1
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0answers
70 views

What does the training time for a Neural Network include?

I recently developed a DNN model and I want to know what exactly is training time and what all steps are included in it? For ex I carried out the following steps 1) Determined best Network ...
0
votes
1answer
37 views

Data preparation for Regression Model

Hi I'm currently trying to predict if an item will be successful in my store, this means (How much is going to sale in USD) My training dataset contains many features: Item name Item weight Item ...
0
votes
1answer
66 views

When it is a good idea to train a model also on the test data?

I have a small restricted dataset, it is not very small but accuracy will be much better if I will have more data. I have split it to train and test datasets: 85%/15%. I have chosen NN model and ...
0
votes
1answer
43 views

Training neural network classifier with one class after another

Is it possible to train a neural network classifier with only one class, and after that with only another class? For example, first train it only on recognizing dogs, and after finishing that ...
1
vote
1answer
230 views

Export dataset with predicted target - Python

I've this code (part of predictive model): ...
7
votes
2answers
2k views

How to fix class imbalance in training sample?

I was very recently asked in a job interview about solutions to fix an imbalance of classes in the training dataset. Let's focus on a binary classification case. I offered two solutions: oversampling ...
1
vote
1answer
100 views

Optimization methods used in machine learning

I don't have too much knowledge in the field of ML, but from my naive point of view it always seems that some variant of gradient descent is used when training neutral networks. As such, I was ...
2
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0answers
609 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 ...
1
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0answers
173 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 ...
3
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0answers
194 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 ...
2
votes
2answers
961 views

validation/training accuracy and overfitting

If we randomly split the data into training data and validation data, and assume the training data and validation data have similar "distributions", i.e. they are both good representations of the ...
7
votes
1answer
5k views

How to train data by batch from disk?

I am working on a convolutional neural network for image classification. The training dataset is too large to be loaded on my computer memory (4gb), on top of that I also need to try some augmentation ...
5
votes
2answers
410 views

Type of images used to train a neural network

I am a newbie in neural network. Saw this article Object detection with deep learning and OpenCV. These three type of neural network are shortlisted in the article Faster R-CNNs You Only Look Once (...
1
vote
1answer
1k views

how should I measure performance if there is no test data?

I have 'practice' data set which I can split into training, validation, and test set and I will play with data to make a machine learning model. But in real situation, I will be given a very small ...
2
votes
3answers
63 views

Are there any frameworks available that allow for automated large scale supervised machine learning?

The typical steps for solving a machine learning/pattern recognition problem: Data Analysis and splitting the data into test and train sets. Choosing a model. Training the model, and testing the ...
1
vote
1answer
331 views

Predict whether or not a user will visit the library tomorrow using historical data

My dataframe contains 7000 rows with the following library login details: login time, libraryid (userid), login date, fined/not. This data is for a local library, I want to create a model which ...
59
votes
2answers
43k views

Training an RNN with examples of different lengths in Keras

I am trying to get started learning about RNNs and I'm using Keras. I understand the basic premise of vanilla RNN and LSTM layers, but I'm having trouble understanding a certain technical point for ...
2
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0answers
35 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 ...
3
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2answers
665 views

Accelerate deep learning model training on several GPUs

I have a deep learning model that can be trained in one GPU, however, is very slow. Is there a way to accelerate the training by parallelizing it across several GPUs? How would be the training process?...
4
votes
2answers
61 views

Will my neural network get lazy if I give it an “easy” feature?

Let's say I start with a standard conv net architecture capable of 99% accuracy on MNIST such as this one, but let's say I merge in an "easy" feature to the fully-connecter layer such as a vector of ...
3
votes
1answer
106 views

When forecasting time series, how does one incorporate the test data back into the model after training?

When you build a classification or regression model, you typically split the data into a train data set and a test data set. The test data is a randomly selected subset of the overall data. Once you ...
2
votes
3answers
202 views

Sentiment Analysis: Train Separate Models or Use One for All

We have been tasked with building an in-house sentiment tool and we are going to use it on a multitude of data sources; survey responses, reviews, social listening etc.. This may be obvious to some ...
0
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1answer
35 views

What is training [closed]

I'm a newbie on deep learning and I have a simple question. I'm reading some article about the neural network. It says that people created a simple neural network named perceptron. And this network ...
0
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1answer
487 views

Creating the optimal set of utterances to train a natural language processing engine

Context I am using natural language processing engines such as IBM's Watson Conversation and Microsoft's LUIS, which take a sentence and classify its intent. For example, "i want to buy food" => "...
1
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1answer
45 views

How to evaluate data capability to train a model?

Bioengineering data comprises of 512 binary features and a single Boolean label: if the particular mixture is worth further research. There are about 1,200,000 results of previous experiments ...
1
vote
1answer
3k views

99% validation accuracy but 0% prediction results (UNET Architecture)

I am debugging results from the UNET architecture that I am using for identifying corneal reflection in eye images. While I am getting over 99% training accuracy and also very high (over 99%) ...
1
vote
2answers
134 views

Where can I find a trained neural network data to play with?

This is the trained neural network for the XOR operator: Can I find something like a trained network for recognizing hand writing digits somewhere on the internet? Is there an "official format" for ...
6
votes
4answers
10k views

Tool to Label Images for Supervised Classification

I have a couple thousand photos of whales taken from drones and I'm planning to build a simple binary classifier to run on these and future images to see if they contain a whale. I'd like to label ...
3
votes
1answer
229 views

Using already trained classifiers in Orange

I know that with Orange it is possible, using the 'Test & Score" widget, to test the performance of a classifier trained on a specific training set using a different test set ('Test on test data' ...
1
vote
2answers
275 views

Do models without parameters exist?

I am reading "A Course in Machine Learning" and, in chapter 2, the author says: "For most models, there will be associated parameters. These are the things that we use the data to decide on. ...
2
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0answers
249 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 ...
2
votes
2answers
1k views

Why exactly using a test set for model evaluation is a bad idea?

I don't understand why using the test set for model evaluation is a bad idea. I completely understand why you should not use your test set to train your model (because in that case, you would be ...
2
votes
2answers
3k views

Training set, validation set, and test set with Orange

Is it possible with Orange (only using its widgets, without writing Python code) to implement the following typical machine learning processes? Train a training set, Validating a validation set (e.g....
2
votes
1answer
604 views

What is Extreme Learning Machine? Why tuning of weights is not required?

The wikipedia says: Extreme learning machines are feedforward neural network for classification, regression, clustering, sparse approximation, compression and feature learning with a single ...
0
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1answer
124 views

Where can I find datasets with labeled duplicate text documents?

I'm working on detecting duplicate text documents using a classifier. I am looking for training data - a corpus of text documents and corresponding metadata which lists out pairs of duplicate ...
0
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0answers
777 views

Neural Network: how to interpret this loss graph?

I have built a deep CNN with TensorFlow that does not classify on one-hot encoded vectors but probability distributions, i.e. given some input $X$ I feed a normal distribution $\mathcal{N}(\mu, \sigma^...
1
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0answers
63 views

How to select samples for a trainings set

My dataset contains half a million unlabeled entries with over 100 binary features. A third of these features are present in less than 1000 samples. I want to classify a few samples by hand (into ...
4
votes
1answer
6k views

How to train an image dataset in TensorFlow? [closed]

As I am new to TensorFlow, I would like to do image recognition in TensorFlow using Python. For this Image Recognition I would like to train my own image dataset and test that dataset. Please answer ...
0
votes
1answer
40 views

Evaluating loss for non classifying convolutional neural network

Sorry if my question is kind of dumb, I am very new to this field. I am trying to create a CNN that plays a variant of chess (for the examples, we'll use chess as it is close enough). My network , ...
5
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1answer
1k 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 ...
0
votes
1answer
901 views

Training the Variational Autoencoder After applying the reparameterization trick

In a Variational Autoencoders, z cannot be simply sampled from the output of the autoencoder directly since the network would not be differentiable. Instead, we have to sample from a normal ...