## What is Random Forest?

Random Forest or Random Decision Forest are an ensemble learning method for classification, regression, and other tasks, that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification) or mean prediction (regression) of the individual trees. Random … Read More

## What is Nearest Neighbor Algorithm?

Nearest Neighbor Algorithm was one of the first algorithms used to determine a solution to the traveling salesman problem. In it, the salesman starts in a random city and repeatedly visits the nearest city until all have been visited. It quickly yields a short tour, but usually not the optimal … Read More

## What is Hierarchical Clustering?

Hierarchical Clustering in data mining and statistics (also called hierarchical cluster analysis or HCA) is a method of cluster analysis which seeks to build a hierarchy of clusters. Strategies for hierarchical clustering generally fall into two types: Agglomerative: This is a “bottom up” approach: each observation starts in its own … Read More

## What is Gini Coefficient?

Gini Coefficient is a measure of statistical dispersion intended to represent the income or wealth distribution of a nation’s residents and is the most commonly used measure of inequality. The Gini coefficient measures the inequality among values of a frequency distribution (for example, levels of income). A Gini coefficient of … Read More

## What is Feature Vector?

Feature vector in pattern recognition and machine learning is an n-dimensional vector of numerical features that represent some object. Many algorithms in machine learning require a numerical representation of objects since such representations facilitate processing and statistical analysis. When representing images, the feature values might correspond to the pixels of … Read More

## What is Feature in machine learning?

Feature in machine learning and pattern recognition is an individual measurable property of a phenomenon being observed. Choosing informative, discriminating and independent features is a crucial step for effective algorithms in pattern recognition, classification, and regression. Features are usually numeric, but structural features such as strings and graphs are used … Read More

## Intro to Machine Learning

Machine Learning Definition The Machine Learning subfield of science provides computers with the ability to learn without being explicitly programmed.  The goal of Machine Learning is to develop learning algorithms that do the learning automatically without human intervention or assistance, just by being exposed to new data, this paradigm can … Read More

## Machine Learning

Machine learning is a subfield of science, that provides computers with the ability to learn without being explicitly programmed.   The goal of machine learning is to develop learning algorithms, that do the learning automatically without human intervention or assistance, just by being exposed to new data. The machine learning paradigm … Read More