All Questions
Tagged with neural-networks multi-class
49 questions
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27
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Reason for softmax approximation in Ian Goodfellow's deep learning book
In section 6.2.2.2 (equation 6.31) they state:
Overall, unregularized maximum likelihood will drive the model to learn parameters that drive the softmax to predict the fraction of counts of each ...
- 11
1
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1
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188
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Multiclass Classification using Binary Representation and Sigmoid Activation in Neural Network
I am currently working on a multiclass classification problem where I have categorical variables that I've encoded using binary representations as follows:
...
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1
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1
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81
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Very balanced dataset and a multiclass classification problem, no context behind the inputs. Which evaluation metric to use?
I have constructed a simple neural network model, for a classification problem, with 10 target classes where an input (with some number of features) is to be classified to only one of the 10 classes.
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1
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1
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1k
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Multi-Label Classification where each label is a Multi-class problem
Problem:
Currently, I have 15 classification models(multi-class + binary). Training and Maintaining 15 models take a huge time and cost. Also, I need to inference 15 models for every input. So I ...
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1
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253
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How to handle with long-tail classification
I have a long tailed distribution with many classes,
and the num of samples per class is
...
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0
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55
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How do I know which class has been difficult to learn for my multi-class model?
For a multi-class model, there are always chances that the model is learning one class's features more than the other. But how do I find which class has been weakly learned? Please help.
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1
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1
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101
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Linear Classifiers -- Single Linear Layer with k Neurons vs 'one vs rest' (k Linear Layers with 1 Neuron)
When using a linear classifier for a k-class classification problem, is there actually any difference of using
a single linear layer with ...
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2
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1
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134
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Train a neural network model that works even if some input features are missing
Background
I am designing a NN model for a multi-class classification problem. The model takes two sets of features, F1 and F2, for making a prediction. However, F2 might be missing in production, but ...
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1
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1
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37
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Should I train my classifier with examples that are outside my classes of interest? And should I create an "others" class to handle them?
This is a 2 part question regarding a multi-class classifier based on a neural network that is expected to predict whether the input image has a cat or a dog. If shown something different (like a man),...
4
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3
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1k
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Effects of class imbalance on neural network weights
My question is about unbalanced classes problem in case of a classifier neural network for natural language processing (in particular, a neural network with LSTM).
I want to train a neural network to ...
1
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0
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184
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Multi-class multi-label with partial mutual exclusivity
Given an input, I want to predict 0/1 for each of N output classes. The output can be 1 for multiple classes. So I'm training with individual binary cross-entropies for each of the output classes. ...
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1
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1
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402
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Can in theory a multiclass neural network classifier be seen as multiple binary neural network classifiers? [closed]
I would like to know more about the theoretical implications of such a statement.
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1
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1k
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What can I do when Overfitting doesn't seem to go away by any means?
So first of all I've seen a lot of overfitting questions around here, but none of the answers seem to improve my model.
I wrote a neural network made without frameworks (only used numpy), and for the ...
- 93
0
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0
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522
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Increasing precision for one label in multiclass classification
I am doing multiclass classification for 3 labell with neural net. The model works fine but when I check precision/recall per label in validation set I can see that precision is a little bit too low ...
- 31
4
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0
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1k
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Categorical cross-entropy vs Binary cross-entropy for multi-class classification with mixup
I understand that for multi-class classification the correct loss to use is categorical cross-entropy. However, when performing mixup as a regularisation technique two samples $(X_1, y_1)$ and $(X_2, ...
- 1,188
0
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1
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714
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Deep Neural Networks to combine regression and multi-class classification problems
I have a dataset obtained from a mobile app which is applicable for regression problem since the output values are numerical. I need to predict the numerical values and then predict their classes (...
1
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1
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163
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What is the best way to eliminate neutral words in a text classifier?
I'm creating a news classifier using the reuters dataset. Right now I'm in the process of preparing the dataset for training. First I removed all punctuation, numbers and special characters and after ...
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1
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1
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502
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Using FCNN for multi-class semantic segmentation trained on single class labeled image data
I am working on project where main task is semantic segmentation of land cover and another objects in Sentinel 2 multi-spectral images. Currently I posses dataset ...
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1
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0
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32
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Which loss function is the best for muticlass ordinal model?
I have a deep-learning model, where you can predict 5 different class (0-4). I want a model that punishes predictions that are more wrong. So if the model predicts 3 and it is a 4, it's not as bad as ...
0
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0
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27
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Neural network performs well on test but classifies completely the opposite when used to classify on training data
I have a neural network that is being used to classify three classes -1, 0, 1. It going to be applied to time series data to determine a class at each time point to ...
- 101
3
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1
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304
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Using pos_weight to improve recall in a multi-class multi-label problem
I have a multi-label classification problem, and so I’ve been using the Pytorch's BCEWithLogitsLoss. I’d like to optimize my model for a higher F2 score, and so want to bias it to have greater recall (...
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1
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1
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2k
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How many data points per class is neccesary to train a multi-class deep learning model?
I have around 20,000 manually categorized texts into 500 classes. Around 150 of the classes have only one instance in the data. If I limit it to classes with at least 4 instances in the data, I get to ...
- 305
1
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0
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184
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How to maximize subset accuracy for multilabel multiclass image classification
I working on multi-label multi-class image classification. I am using TensorFlow.
Currently I am using sigmoid on output layer with binary_crossentrpy. Model is ...
- 111
0
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0
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595
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Why not approach the Multi-Class Classification problem using Neural Networks as a model the same way it's approached with a Logistic Regression model
I can't seem to understand why when approaching a K-class classification problem using a Neural Network we take a different approach than any other classification model.
I understand that in the ...
2
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0
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538
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Similarity between Train and Test data sets
I have multiclass classification dataset and I am using Deep nets for the classification task. To explain the problem, let's assume that I have 5 classes to classify. No matter what I try, be it ...
- 199
1
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0
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499
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Multi-class image segmentation with conflicting labels
I'm trying to perform multi-class semantic segmentation on a corpus made up of several sub-corpora. The difficult part is that across sub-corpora labels are not consistent. That is to say that similar ...
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2
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1
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7k
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Handle categorical class labels for scikit-learn MLPClassifier
I have a handwritten dataset for classification purpose where the classes are from a-z. If I want to use MLPClassifier, I think I cannot use such categorical ...
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1
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1
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91
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Neural Networks: How to do class prediction from murky labels
I'm conducting an experiment with the MNIST digit data - handwritten digits 0-9, each example composed of 28x28 bitmap of pixels.
Imagine a collection of examples is drawn at random without class ...
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1
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1
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527
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Conceptual question on MLP error calculation
Consider a NN of 2 input neurons, one hidden layer of 4 neurons and one output node. The task is to predict the next sample given two input samples at a time. $m_1$ is the output of the hidden layer, $...
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3
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1
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2k
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Loss function and activation function for categorical AND multi-label classification in neural network?
I am training a neural network to classify a set of objects into n-labels, each label with m different category. E.g. for n = 5, and m = 3, an example output is [0,2,0,2,1].
I can also transform the ...
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0
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545
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What is a good loss function in multiclass multilabel classification where only one of the possible labels is observed?
I am training an ANN in multiclass multilabel scenario, where only one of the possible labels is observed at a time, let me illustrate on an example:
I have a state X and the ground truth label Y for ...
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9
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1
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8k
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Multi-label or multi-class...or both?
I'm having a hard time getting the difference between multi-class and multi-label classification with CNNs.
My understanding is that if I want to
classify different breeds of dogs, that is a multi-...
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1
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1
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267
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Neural Network and H2O.ai: inputs that have multiple right answers (questions about a previously answered question)
I have two questions related to this previously answered question.
Can someone explain how the NN's backproagation algorithm would not be able to function properly when inputs have multiple right ...
1
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0
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145
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Learning separate models vs single model
I have seen in several texts that: "We learn separate models for each class/category". What does this mean and how is this different from learning a single model to classify all the classes?
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4
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2
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2k
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(Deep learning) classification confidence
I have a model that is trained on n classes and has more than 95% accuracy on the test set.
The model is going to receive a mixture of images that are either from ...
- 163
2
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1
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88
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How to decide what algorithm I should use?
Some background - I am a Computer Science student, planning to do a project and I have a data source that I have cleared, filtered and processed but I am really unsure of what exact algorithms I ...
1
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1
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329
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Multiple multiclass classification
Let's say we need to recognize 5-digit zip code from an image, and we want to do that without any sliding window.
If we use 5 Keras models to recognize each digit ...
1
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1
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949
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Classification - train on full data, predict on partial data
I have a dataset X which consists of two parts: X1 and X2. X2 is believed to depend on X1. And there is a resulting dataset Y which depends on both X1 and X2. For every training sample X1 and X2 are ...
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10
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2
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8k
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Neural network for multi label classification with large number of classes outputs only zero
I am training a neural network for multilabel classification, with a large number of classes (1000). Which means more than one output can be active for every input. On an average, I have two classes ...
- 111
5
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1
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4k
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How do I use negative examples (in addition to positive ones) for training a multiclass softmax classifier (or a neural net with softmax output)?
Suppose we are training a neural network for multi-class classification, and we use softmax (or hierarchical softmax) as its output layer.
For positive examples, we need to maximize the log ...
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3
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19k
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How to apply Softmax as Activation function in multi-layer Perceptron in scikit-learn? [closed]
I need to apply the Softmax activation function to the multi-layer Perceptron in scikit. The scikit documantation on the topic of Neural network models (supervised) says "MLPClassifier supports multi-...
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3
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1
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299
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Training N classifiers for N labels vs one classifier with N labels
I have a classification problem which is multi-label with N labels. I would like to know which method would be the better choice? Training N classifiers (1 for each label) or a single classifier which ...
- 133
0
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1
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430
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How to operate on a count dataset (positive whole numbers with a lot of zeros) using neural networks for classification?
So i have some dataset, which is basically a count dataset. I have my own code for the classification using neural networks. Turns out that the data does not have a lot of correlation so accuracies as ...
4
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1
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601
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What are proper scoring and threshold selection rules for multiclassifiers?
I am using a neural network with 5 input neurons, 2 hidden layers of about 50 neurons in each layer, and 4 output neurons, trying to classify my 5-dimensional data into 4 different classes.
Currently,...
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2
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2
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2k
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Detect multiple classes in an image?
I have a deep neural network trained with data of different kinds of fruits (apples, oranges, guava, pear, etc.). In my testing data, I have multiple fruits in the same image. For example, an image ...
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1
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1
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92
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Quadratic error for multi-class classification
I'm trying to train a neural network to classify handwritten inputs into 10 categories, each for one digit (1,...,9,0). I represent the output of an example using a 10-dimensional vector. Digit 5, for ...
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13
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6
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9k
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What is the difference between Multitask and Multiclass learning
Consider a image labeling problem, where I need to assign one or more labels to an image. The possible labels are human, moving ,...
- 2,534
3
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1
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3k
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Negative samples on multiclass neural network training
I want to train a deep neural network to classify images.
In every implementation I have seen, multiclass training uses only the positive examples for each class.
Is there any way to utilize ...
- 201
1
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1
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117
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Limit multiclassification SVM - ANN
I have some questions on the limits of SVM and ANN for multiclass problem.
I know about "one vs all" and "all vs all" strategies but I only want to know the limit of a unique SVM and ANN.
Is there a ...
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