Predicting NBA winners with Decision Trees and Random Forests in Scikit-learn

Predicting NBA winners with Decision Trees and Random Forests in Scikit-learn

In this blog, we will be predicting NBA winners with Decision Trees and Random Forests in Scikit-learn.The National Basketball Association (NBA) is the major men’s professional basketball league in North America and is widely considered to be the premier men’s professional basketball league in the world. It has 30 teams (29 in the United States...

Naiive Bayes in scikit-learn

Naïve Bayes is a simple but powerful classifier based on a probabilistic model derived from the Bayes’ theorem. Basically it determines the probability that an instance belongs to a class based on each of the feature value probabilities. One of the most successful applications of Naïve Bayes has been within the field of Natural...

Support Vector Machine in scikit-learn- part 2

Support Vector Machine in scikit-learn

continued from part 1 In : print_faces(faces.images, faces.target, 400) Training a Support Vector Machine Support Vector Classifier (SVC) will be used for classification The SVC implementation has different important parameters; probably the most relevant is kernel, which defines the kernel function to be used in our classifier In : from sklearn.svm import SVC svc_1 = SVC(kernel='linear')...