Bias is the difference between actual value and the predicted value that a model predicts. In machine learning, data is fed to the machine learning model, the model finds the patterns from data and learns from data.
Imbalance dataset is such a type of dataset that has an unequal distribution of data among the classes of classification of datasets. Most machine learning algorithms work well with balanced datasets.
K-Nearest Neighbor(KNN) algorithm is a supervised machine learning algorithm that is used for classification and regression analysis.
k-means clustering is an easy yet powerful algorithm in machine learning that is used for clustering the data in different clusters. It is centroid based clustering in machine learning.
Hyperparameter tuning is an essential term in the field of machine learning. Hyperparameter is a set of parameters that control the learning process of the algorithm.
Feature scaling is one of the important step in data pre-processing. Scaling refers to converting the original form of data to another form of data within a certain range. Many machine learning models perform well when the input data are scaled to the standard range