Performance Evaluation of Decision Trees with Machine Learning Algorithm

Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. Decision trees are considered to be one of the most popular approaches for representing classifiers. Researchers from various disciplines such as statistics, machine learning, pattern recognition and Data Mining have dealt with the issue of growing a decision tree from available data. Decision trees in machine learning will be used for classification problems, to categorize objects to gain an understanding of similar features. Decision trees helps in decision-making by representing complex choices in a hierarchical structure. Every node in decision tree verifies specific attributes, guiding decisions based on different data values in the dataset. Leaf nodes provide final outcomes and result which gives a clear and interpretable path for decision analysis in machine learning. Therefore implementation of Decision tree algorithm using python is presented in this paper