Searching for data stored in different data structures is a crucial part of pretty much every single application.
There are many different algorithms available to utilize when searching, and each have different implementations and rely on different data structures to get the job done.
Being able to choose a
A decision tree is one of most frequently and widely used supervised machine learning algorithms that can perform both regression and classification tasks. The intuition behind the decision tree algorithm is simple, yet also very powerful.
For each attribute in the dataset, the decision tree algorithm forms a node,
The K-nearest neighbors (KNN) algorithm is a type of supervised machine learning algorithms. KNN is extremely easy to implement in its most basic form, and yet performs quite complex classification tasks. It is a lazy learning algorithm since it doesn't have a specialized training phase. Rather, it uses all of
In an earlier article I gave you an introduction into phonetic algorithms, and shows their variety. In more detail we had a look at the edit distance, which is also known as the Levenshtein Distance. This algorithm was developed in order to calculate the number of letter substitutions to get
There are two types of supervised machine learning algorithms: Regression and classification. The former predicts continuous value outputs while the latter predicts discrete outputs. For instance, predicting the price of a house in dollars is a regression problem whereas predicting whether a tumor is malignant or benign is a classification
