In machine learning and statistics, classification is the problem of identifying which of a set of categories a new observation belongs to, on the basis of a training set of data containing observations whose category membership (label) is known.
I'm trying to understand GMM by reading the sources available online. I have achieved clustering using K-Means and was seeing …
matlab machine-learning classification cluster-analysis mixture-modelDoes any one know how to set parameter of alpha when doing naive bayes classification? E.g. I used bag …
python scikit-learn classification naivebayesI can't figure out if I've setup my binary classification problem correctly. I labeled the positive class 1 and the negative 0. …
python machine-learning scikit-learn classificationI understand the differences between supervised and unsupervised learning: Supervised Learning is a way of "teaching" the classifier, using labeled …
machine-learning classificationI have a decision tree that i need to turn to a code in C# The simple way of doing …
c# .net classification decision-treeI am extracting image features from 10 classes with 1000 images each. Since there are 50 features that I can extract, I am …
machine-learning computational-geometry classification knnI'm working on a project that would show the potential influence a group of events have on an outcome. I'm …
r classification glm cross-validation glmnetI'm working on a particular binary classification problem with a highly unbalanced dataset, and I was wondering if anyone has …
apache-spark machine-learning classification apache-spark-mllibI know that Cross validation is used for selecting good parameters. After finding them, i need to re-train the whole …
matlab machine-learning classification svm libsvmI can't for the life of me figure out how to compute a confusion matrix on rpart. Here is what …
r machine-learning classification decision-tree confusion-matrix