Questions tagged [multiclass-classification]

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proper activation function at output and loss function to optimize for OCR?

I am trying to make a CNN model on IAM handwritten words data(which has images of words handwritten by multiple people and targets are text in the images). So, I can encode words to numbers(A=0, B=1 ...
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Why my training and testing set are about 99% but my single prediction does wrong prediction?

I have performed fruits classification using CNN but i am paused at a point where all things are going right confusion matrix accuracy score all are correct it seems there is no overfitting but it ...
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34 views

Understanding output probabilites of xgboost in multiclass problems

I would like to understand the output probabilities of a xgboost classifier (or any other decision tree ensemble based classifier) in the case of a multiclass problem. For example: We have 5 different ...
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Text Classification : Classifying N classes vs rest of the classes

Apologies if this is naive, I am fairly new to the domain. I have a requirement where I am trying to classify 2 types of text data, i.e, I have got 2 classes to classify my data upon. I am able to get ...
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Appropriate loss function for multi-hot output vectors

I have some data in which model inputs and outputs (which are the same size) belong to multiple classes concurrently. A single input or output is a vector of zeros somewhere between one and four ...
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39 views

How to train a machine learning algorithm with multiple labels

I have the following challenge and I very much hope that there is a solution to it. I also suspect that there is a simple approach to it. I just don't see it at the moment. Any help or advice is ...
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Time Series Data Multi-Class Classification

This is a very general question, as I'm still very much in the learning phase with machine learning. I have some utility data around problematic meters. Even tho the data is "time series", I believe ...
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per class IOU & Jaccard Similarity in a Multiclass setting python

For a multiclass classification problem, How do you compute per class IOU ? I am using the formula which is referenced/accepted in the below link ...
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dealing with imbalanced data for multi-class problem

Based on the experiments I run for a number of times, and the reading I did on imbalanced data for a multiclassification problem such as this paper, resampling techniques like ...
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How do people deal with significantly uneven error in NNs

The following example is a common issue with multiclass classification problems: If we try to classify an object - let's say - by color (e.g. white, red, green, blue, black, transparent), a simple ...
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multiclassification dataset with many features giving very bad accurace predictions

I have been trying to fix this for 2 months now with no luck. I am doing some medical research for my study. I have a dataset that has patients diagnosis based on medical reports (Features.csv) and ...
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Derivative of multi-output Gaussian Process

I am working on a project where I estimate transition and measurements models for a kalman filter using Gaussian Processes. In order to linearize the models I require the Jacobian of the estimated ...
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34 views

How to cope with new/unseen targets classes in incremental learning algorithms

According to scikit-learn documentation1, the sklearn incremental learner itself may be unable to cope with new/unseen targets classes. Is there any available python machine learning library which ...
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Time series multiclassification on process measured multiple times

I have been measuring the power usage of a 3D printer for a while. To create a dataset I've measured the power usage of the printer during different printing processes a few times. The data is ...
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How could a neural network classifer for multilclass problem classify only in one class when a decision tree is more balanced and accurate?

I want to create a classifier for a data frame that has four classes. Each line can only have one class. I have two predictive models: a neural network and a tree classifier. But they put everyone in ...
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1answer
32 views

Confusion around categorical cross entropy

I understand the binary cross entropy formula for a problem with a single label 0 or 1. If we have more than 2 labels we sum this binary cross entropy over all these classes. $$ H_{y'}(y) := - \sum_{...
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36 views

How to best summarize and visualize the outcome and performance of a multi-class problems?

I estimate a multi-class origin-destination model with 45 classes. In particular the classes are geographical regions between which people can move. Currently I summarize the overall performance using ...
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Do I have to wrap multiclass SVM in OneVsRestClassifier()?

I am using an SVM for mulitclass classification between 3 labels (1,0,-1). I thought this could simply be done by using SVC(decision_function_shape = 'ovr') in my ...
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34 views

How to compute AUC in gridsearchSV (multiclass problem)

I'm working on a multiclass classification problem, comparing results from SVM and Random Forest classificators. I would like to use gridsearchCV for hyperparameters tuning and find that AUC is the ...
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ML.net Text Feature Augmentation and Selective Normalisation

I'm in the middle of training a model for multi-class classification, I'm relatively green here and have a few questions for the more seasoned among you. Is it possible to progmatically add a line ...
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1answer
28 views

Multi-class classification with only one feature

I am studying the efficacy of using a single feature for predicting a set of events (which is a multi-class classification problem). I was wondering if it makes any sense to use only one feature for ...
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Upsell project based on sales records

in my company we are working on a upset project in which we are trying to solve the following problem: What we propose to our customer that he/she may be interested in based on the fact that he/she ...
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1answer
37 views

How is the weight matrix set and its dimension in CNN

I am trying to calculate the output size of each layer and the number of parameters for 3 class classification using CNN. I have calculated till the final maxpooling layer and would really appreciate ...
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56 views

How to deal with broad and narrow variance within classes in classification tasks

Let's say I'm doing an animal image classification task (it doesn't have to be image classification - this is just my example), and the training and test data is balanced across classes. The classes ...
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80 views

XGBoost multiclassification interpreting predicted probabilities

Let's consider an example. I have patient level data, their symptoms, reading from various medical tests. Based on that, I have built a binary classifier given patient data to classify if they are ...
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149 views

Generate a balanced batch with ImageDataGenerator() and flow_from_directory()

Hi I am new to python and deep learning. I am doing a multiclass classification. My 3-classes dataset is imbalanced, the classes take about 50%, 40%, and 20%. I am trying to generate mini batches with ...
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Multiclassification problem [closed]

I was wondering what happens when an image not in the training set is provided to the model in a multiclassification problem? Does it just classify something which is close to this image?
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How to deal with training set that overfits very easily

I have a dataset consisting of 72 one-hot encoded (thus binary) features and 2.5K training examples. With this I am trying to solve a 10-class classification problem. My main problem is that no ...
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52 views

Different definitions of Macro F1 score, which one is used in Scikit-learn?

In this article Macro F1 and Macro F1 two different definitions of the F1 used in the literature are demonstrated. The first F1 score is computed such as: F1 scores are computed for each class ...
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Multi-class classification with discrete output: Which loss function and activation to choose?

I'm working with a multi-class classification problem, using Keras Sequential models. In my dataset, the output class has one of the following values: ...
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1answer
25 views

Control which features are used for every task in multioutput classification?

I would like to perform a multiclass-multioutput classification task, on vectorized textual data. I started by using a random forest classifier in a multioutput startegy: ...
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How Hyper-linked library vs traditional library differs from each other as ML problem?

Traditional library can be understood as a system, that archives the collective information from the mediums produced by our society, by indexing them to shelves. It is assumed that libraries have ...
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Multiclass imbalanced classification

I have a dataset with the target variable having 3 classes. Value counts of Target variable are as follows: ...
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258 views

AUC-ROC for Multi-Label Classification

Hey guys I'm currently reading about AUC-ROC and I have understood the binary case and I think that I understand the multi-classification case. Now I'm a bit confused on how to generalize it to the ...
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How to prepare data for multi-class tasks

I wish to train a multiclass audio classification NN. I am following this paper and this tutorial. The thing is, for audio segments containing more than a single class, ...
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1answer
97 views

LSTM Multi-class classification for large number of classes

I want to build a model that classifies 473 classes -product categories-, but I'm facing a problem with loss not decreasing. Data I have almost 3,000 data points for each class -473 classes- (data ...
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statistical hypothesis and rejection

Recently I have to analyze the multiclass classification problem But, it's not just I have to predict and submit I have to make a hypothesis with this data and have to find the rejection methods for ...
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is there metric 'multi_logloss' for xgb crassifier?

lgb has the log_loss metric ...
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1answer
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Over/Under Sampling for Multi-classification

I'm trying to apply xgboost and random forest for over and under sampling For imbalanced data: train shape -> (199991, 23) However, reverse my expectation. ...
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96 views

Association rule learning for multi-classification suggestions

The task is the following: given a training set of medical symptoms and an associated diagnosis, output a list of the most likely diagnosises for a combination of symptoms. As of now, a solution ...
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Different performance for splitting into test/train data vs. using cross-validation

I am training a linear model using the following scikit-learn setup: ...
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Sequential Forward Selection (SFS) for standard Feed Forward Neural Network

I'm comparing the classification performance (accuracy, f1-score etc.) of several predictive models (logistic regression, random forest, xgboost etc.) with a standard feedforward neural network. For ...
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140 views

How to apply supervised machine learning when the target label depends on multiple input rows?

The problem is a multi-label classification problem. Now, I know how to train and classify using single row with several attributes. For example, if the dataset looks like the first table from the ...
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Multiclass AUC score higher than binary

I just built a random forest classifier and wondered about the results. I have 4 classes: A, B, C and control. When I compare A vs control, B vs control, C vs control I get a lower average AUC score ...
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29 views

Multiclass classification task where each class is present only once in the test set

I have a multiclass classification problem where, in the test set, there is only one entry for each possible class. In my particular problem we want to guess the author of a text, and we have 20 ...
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1answer
26 views

Several independent variables based on the same underlying data

I got a data containing, among others, two feature variables, which are based from the same underlying data (i.e. have mutual information), but they convey different information/message. How to handle ...
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Unbalanced data set - how to optimize hyperparams via grid search?

I would like to optimize the hyperparameters C and Gamma of an SVC by using grid search for an unbalanced data set. So far I have used class_weights='balanced' and selected the best hyperparameters ...
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1answer
44 views

How to estimate the accuracy on a large dataset?

Given that I have a deep learning model(handover from former colleague). For some reason, the train/dev set was missing. In my situation, I want to classify my dataset into 100 categories. The ...
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1answer
25 views

multiclass classification

I want to build an ml model, which can when given a text input, can predict predefined tags or labels for the text. I already built one such model, but the problem with that is that it only predicts ...
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34 views

Use cross entropy to create decision tree classifier

Are entropy and cross-entropy the same thing as per basic definition? If there is a difference: Decision tree splits take on entropy or Gini index, can we use cross-entropy to split decision trees? ...

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