What is Clustering? Clustering, or cluster analysis is a machine learning techniques that groups the unlabeled dataset. It can be defined as “a way of grouping data points into different clusters,...
Random Forest Classification
What is Random Forest Classification? Its basic algorithm is the same as Random Forest Regression except that predicting a value sets a category. Example Code from sklearn.ensemble import Ra...
Decision Tree Classification
What is Decision Tree Classification? It’s basic algorithm is the same as Decision Tree Regression. The difference can be seen in the image below. Decision Tree Classification Decision Tree R...
Naive Bayes
What is Bayes? Bayesian analysis is a statistical paradigm that answers research questions about unknown parameters using probability statements. It can be expressed in the following formula: $ P...
Kernel Support Vector Machine(Kernel SVM)
What is Kernel SVM? It is a concept that was developed to compensate for the disadvantage that SVM cannot handle non-linear datasets like image below. So, how does Kernel SVM classify non-li...
Support Vector Machine(SVM)
What is SVM? Like Support Vector for Regression (SVR), there is a straight line called the Maximum Margin between two categories. The Maximum Margin Hyperplane is drawn equidistant from the two ne...
K Nearest Neighbors(KNN)
What is KNN? KNN categorizes new values into the category that has a majority among the K nearest neighbors. To Steps of KNN Step 1. Choose the number K of neighbors. Let’s assu...
Logistic Classification
What is Logistic Regression? Logistic regression is an example of supervised learning. It is used to calculate or predict the probability of a binary event occurring. Let’s assume that you have a ...
Classification
What is Classification? Classification is defined as the process of recognizing, understanding, and grouping objects and ideas into preset categories. With the help of these pre-categorized trainin...
Random Forest Regression
What is random forest regression? Random forest regression is a type of ensemble learning, which is the process of using multiple models, trained over the same data, averaging the results of each ...