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Questions tagged [multiclass-classification]

Multi-class classification is when you have a classification problem with multiple classes, specifically 3 or more classes. Many classifications are binary by design, therefore the additional nomenclature of multi-class classification was defined to describe algorithms capable of classifying datasets with more than 2 classes.

Multi-class classification is when you have a classification problem with multiple classes, specifically 3 or more classes. Many classifications are binary by design, therefore the additional nomenclature of multi-class classification was defined to describe algorithms capable of classifying datasets with more than 2 classes.

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Micro Average vs Macro average Performance in a Multiclass classification setting

I am trying out a multiclass classification setting with 3 classes. The class distribution is skewed with most of the data falling in 1 of the 3 classes. (class labels being 1,2,3, with 67.28% of the data falling in class label 1, 11.99% data in…
SHASHANK GUPTA
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Unbalanced multiclass data with XGBoost

I have 3 classes with this distribution: Class 0: 0.1169 Class 1: 0.7668 Class 2: 0.1163 And I am using xgboost for classification. I know that there is a parameter called scale_pos_weight. But how is it handled for 'multiclass' case, and how can…
shda
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Keras Multiple “Softmax” in last layer possible?

Is it possible to implement mutiple softmaxes in the last layer in Keras? So the sum of Nodes 1-4 = 1; 5-8 = 1; etc. Should I go for a different network design?
cgn.dev
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Deep network not able to learn imbalanced data beyond the dominant class

I have data with 5 output classes. The training data has the following no of samples for these 5 classes: [706326, 32211, 2856, 3050, 901] I am using the following keras (tf.keras) code: class_weights =…
dbm
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How does Sigmoid activation work in multi-class classification problems

I know that for a problem with multiple classes we usually use softmax, but can we also use sigmoid? I have tried to implement digit classification with sigmoid at the output layer, it works. What I don't understand is how does it work?
bharath chandra
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Which comes first? Multiple Imputation, Splitting into train/test, or Standardization/Normalization

I am working on a multi-class classification problem, with ~65 features and ~150K instances. 30% of features are categorical and the rest are numerical (continuous). I understand that standardization or normalization should be done after splitting…
Sarah
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How to apply class weight to a multi-output model?

I have a model with 2 categorical outputs. The first output layer can predict 2 classes: [0, 1] and the second output layer can predict 3 classes: [0, 1, 2]. How can I apply different class weight dictionaries for each of the outputs? For example,…
Gal Avineri
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Earlystopping in multi-output deep learning

When working with a neural network with more than one output, what is generally advised as the best strategy for early-stopping the training process? Given that I am currently monitoring the net validation loss (validation loss from n different…
didgeridoo92
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What is the best method for classification of time series data? Should I use LSTM or a different method?

I am trying to classify raw accelerometer data x,y,z to its corresponding label. What is the best architecture for best results? Or, does anyone have any suggestions on LSTM architectures built on keras with input and output nodes?
rosy
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weighted cross entropy for imbalanced dataset - multiclass classification

I am trying to classify images to more then a 100 classes, of different sizes ranged from 300 to 4000 (mean size 1500 with std 600). I am using a pretty standard CNN where the last layer outputs a vector of length number of classes, and using…
Itaysason
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Text-Classification-Problem: Is Word2Vec/NN the best approach?

I am looking to design a system that given a paragraph of text will be able to categorize it and identify the context: Is trained with user generated text paragraphs (like comments/questions/answers) Each item in the training set will be tagged…
Shankar
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SGDClassifier: Online Learning/partial_fit with a previously unknown label

My training set contains about 50k entries with which I do an initial learning. On a weekly basis, ~ 5k entries are added; but the same amount "disappears" (as it is user data which has to be deleted after some time). Therefore I use online learning…
swalkner
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Products classification by name

I am a beginner with machine learning, and I'm trying to build a model to classify products by category according to the words present in the product name. My goal is to predict the category of some new product, just by observing the categories for…
elias
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Why class weight is outperforming oversampling?

I am applying both class_weight and oversampling (SMOTE) techniques on a multiclass classification problem and getting better results when using the class_weight technique. Could someone please explain what could be the cause of this difference?
Sarah
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Imbalanced data causing mis-classification on multiclass dataset

I am working on text classification where I have 39 categories/classes and 8.5 million records. (In future data and categories will increase). Structure or format of my data is as…
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