Many different aspects of data mining and machine learning seem incredibly complicated. They use variables and mathematical models that appear opaque at first. However, all of these tools have a simple series of goals. They want to make sense of data through either sorting or predictions. Once a newcomer understands…

# Algorithms

Start learning machine learning algorithms used in R tutorials such as Apriori Algorithm, Artificial Neural Networks Algorithm, Decision Trees Algorithm, K Means Clustering Algorithm, K-nearest Neighbors Algorithm (KNN), Linear Regression Algorithm, Logistic Regression Algorithm, Naive Bayes Classifier Algorithm, Random Forests Algorithm, and Support Vector Machine Algorithm.

Many machine learning applications have to create precise categories. Knowing the categories information is in is critical for suitable prediction and sorting. They can turn a jumbled set of numbers into a coherent group as well as a linear regression line or a group of means. The naive Bayes classifier…

Data mining algorithms have been used with many kinds of data and for many purposes. Some have been used to improve on the work and analysis of others. An example of an updated form of machine learning algorithm is the Random Forests algorithm. Random Forests is basically an update of…

There are a number of machine learning algorithms in the world that have a vast number of uses. Few of these algorithms have the same utility, however, as the support vector machine. A support vector machine may not sound as simple or as straightforward as a decision tree or a…