All Questions
17 questions
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44
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VotingClassifier only supports binary or multiclass classification. Multilabel and multi-output classification are not supported
I got an error about KerasClassifer and VotingClassifer.
At the first, I used MNIST dataset and split it then fit xtrain and ytrain by Voting classifer. If I put their estimator type into Classifier ...
- 23
0
votes
1
answer
121
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How to prioritise certain output in MultiOutput LSTM Tensorflow?
Basically, I am creating an LSTM model with Tensorflow and the shape of my input data is something like
(10000 users, 6 timesteps, 20 feature columns) => (10000,6,20)
The model is doing a binary ...
- 35
0
votes
0
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478
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Choosing a multi-label classifier with high number of labels
First of all, I'm very new to ML and I have this task:
I need to build a ML model to give clients a list of 10 professions for each of them which best fit with their data: bachelor's degree type, ...
user15468984
0
votes
1
answer
276
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Improve results for a multi-label text classification problem using deep learning [closed]
I am using deep learning with keras for multi-label text classfication. However, the accuracy i am getting is only between 73-75. I think i am misjudging one of the parameters here. Is there a way to ...
- 1,209
0
votes
1
answer
346
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Is it technically wrong to use simple "accuracy" in keras model metrics for multi-class classification? Should we use CategoricalAccuracy()?
So according to Keras definition, simple "accuracy" metrics compare 2 labelled Classes is that correct.
code snippet
---------some model layers---------.
model.add(Dense(len(...
- 213
0
votes
0
answers
423
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multi-class multi-dimensional label classification in keras
If I have a binary classification task, the last layer of a neural network should be:
output= tensorflow.keras.layers.Dense(1,activation='sigmoid')(x)
model.compile(loss='binary_crossentropy')
If the ...
- 5,389
2
votes
0
answers
301
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How do you train a neural network to predict a set number of labels for every input?
I am working on a project where we are trying to classify gene expression using a neural network. We are using Keras. We have the sequences of 35000 genes. For each of these genes, we know how much ...
- 31
1
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2
answers
34
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How can I add specific numbers of each classification that my NN can predict?
I have an np-array something like one-hot-encoding with 0-1. For each sample I always have 15 zeros and 5 ones. What can I do to make it predict 5 ones and 15 zeros only? I am using the keras library ...
0
votes
1
answer
33
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How to improve accuracy when outputs not equiprobable?
I have a classifier of images that each have exactly one of 5 labels [0-4]. I have hit an accuracy wall at ~72% and am looking for a way over it. I have noticed that my classes [in my training set] ...
6
votes
1
answer
3k
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Keras multi-label image classification with F1-score
I am working on a multi-label image classification problem with the evaluation being conducted in terms of F1-score between system predicted and ground truth labels.
Given that, should I use loss="...
- 5,390
0
votes
1
answer
555
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Multilabel classification of a sequence, how to do it?
I am quite new to the deep learning field especially Keras. Here I have a simple problem of classification and I don't know how to solve it. What I don't understand is how the general process of the ...
- 324
7
votes
2
answers
12k
views
Multi-label classification Keras metrics
Which metrics is better for multi-label classification in Keras: accuracy or categorical_accuracy? Obviously the last activation function is sigmoid and as loss function is binary_crossentropy in this ...
- 323
4
votes
0
answers
2k
views
Training multi-label classifier with unbalanced samples in Keras
I'm trying to train a keras model that takes in samples, let's say x_i for sample i, and predicts multiple independent labels, {y_hat}_ij, such that {y_hat}_ij = 1 if the model predicts sample x_i to ...
- 1,088
0
votes
1
answer
522
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Keras multi-label time-series classification considering time-series as an input image vector
I am trying to build a multi-class classifier using Keras. I am not quite sure I have implemented it correctly.
Data is like this
label time-series variables [0:25728}
index 0 1 2 3 4 ...
- 575
3
votes
2
answers
1k
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How does Keras update weights in multilabel learning (implementation-wise)
Let's say I want to solve a multi-label problem using neural networks and Keras.
The outputs are typically of the form y=[0, 1, 0, 1, 0, 0], and it's easily possible to train a network using binary ...
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