I am working on a classification project that an outcome may belong to multiple classes. For example, the outcomes may belong to Class A, B, and/or C; e.g., A, B, A&B, A&C, B&C, etc. Ho...

I know that you can set scale_pos_weight for an imbalanced dataset. However, How to deal with the multi-classification problem in the imbalanced dataset. I have gone through https://datascience.sta...

I am running a multi-class model(total 40 class in total) for 2000 epochs. The model is running fine till 828 epoch but at 829 epoch it is giving me an InvalidArgumentError (see the screenshot belo...

How to transform vectors of labels to one-hot encoding and back in Pytorch? The solution to the question was copied to here after having to go through the entire forum discussion, instead of just f...

General Explanation: My codes work fine, but the results are wired. I don't know the problem is with the network structure, or the way I feed the data to the network, or anything else. I am str...

I am dealing with a classification problem with 3 classes [0,1,2], and imbalanced class distribution as shown below. I want to apply XGBClassifier (in Python) to this classification problem, but t...

I was wondering how to run a multi-class, multi-label, ordinal classification with sklearn. I want to predict a ranking of target groups, ranging from the one that is most prevalant at a certain lo...

Can someone please explain (with example maybe) what is the difference between OneVsRestClassifier and MultiOutputClassifier in scikit-learn? I've read documentation and I've understood that we u...

I'm doing different text classification experiments. Now I need to calculate the AUC-ROC for each task. For the binary classifications, I already made it work with this code: scaler = StandardScal...

Can anyone explain how to calculate the accuracy, sensitivity and specificity of multi-class dataset?

I have a classification problem where I have the pixels values of an 8x8 image and the number the image represents and my task is to predict the number('Number' attribute) based on the pixel values...

I am doing multiclass/multilabel text classification. I trying to get rid of the "ConvergenceWarning". When I tuned the max_iter from default to 4000, the warning is disappeared. However, my mode...

I'm trying to apply Conv1D layers for a classification model which has a numeric dataset. The neural network of my model is as follows: model = tf.keras.models.Sequential() model.add(tf.keras.layer...

How do you find the F1-score for each class of a multiclass Catboost Classifier? I've already read through the documentation and the github repo where someone asks the same question. However, I am ...

I trained a deep learning model to classify the given images into three classes. Now I want to add one more class to my model. I tried to check out "Online learning", but it seems to trai...

I am trying to explore the working of Xgboost binary classification as well as for multi-class. In case of binary class, i observed that base_score is considered as starting probability and it also...

I am doing a multiclass prediction with random forest in Spark ML. For this MulticlassClassificationEvaluator() in spark ML, is it possible to get precision/recall by each class labels? Currently...

Consider a three class classification problem with the following confusion matrix. cm_matrix = predict_class1 predict_class2 predict_class3 ______________ ______________ ______________ Actual_...

I am trying to model a classifier for a multi-class Classification problem (3 Classes) using LightGBM in Python. I used the following parameters. params = {'task': 'train', 'boosting_type': 'gbdt...

In relation to the previous post on stackoverflow Model() got multiple values for argument 'nr_class' - SpaCy multi-classification model (BERT integration) in which my problem partialy have...

Hi I am working on implementing a multi-classification model (5 classes) with the new SpaCy Model en_pytt_bertbaseuncased_lg. The code for the new pipe is here: nlp = spacy.load('en_pytt_bertbaseu...

I am building a multiclass model with Keras. model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy']) model.fit(X_train, y_train, batch_size=batch_size, epochs=...

How do you compute the true- and false- positive rates of a multi-class classification problem? Say, y_true = [1, -1, 0, 0, 1, -1, 1, 0, -1, 0, 1, -1, 1, 0, 0, -1, 0] y_prediction = [-1, -1,...

I'm trying to know which loss function uses XGBoost for multi-class classification. I found in this question the loss function for logistic classification in the binary case. I had though that for...

I have multi-class classification using RNN and here is my main code for RNN: def RNN(x, weights, biases): x = tf.unstack(x, input_size, 1) lstm_cell = rnn.BasicLSTMCell(num_unit, forget_bias=1...