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artificial intelligence

Use Cases of AI in Data Mining Algorithm

These systems take inputs from a collection of cases where each case belongs to one of the small numbers of classes and are described by its values for a fixed set of attributes.

C4.5 Algorithm

k-means creates k groups from a set of objects so that the members of a group are more similar. It’s a popular cluster analysis technique for exploring a dataset.

k-means Algorithm

In data mining, E is generally used as a clustering algorithm for knowledge discovery. EM is simple to implement.

Expectation-Maximization Algorithm

kNN is a classification algorithm. However, it differs from the classifiers previously described because it’s a lazy learner.

k-Nearest Neighbors Algorithm

This algorithm is based on the Bayes theorem. This is mainly used when the dimensionality of inputs is high. This classifier can easily calculate the next possible output.

Naive Bayes Algorithm

CART stands for classification and regression trees. It is a decision tree learning technique that outputs either classification or regression trees.

CART Algorithm

PageRank is a link analysis algorithm designed to determine the relative importance of some object linked within a network of objects.

PageRank Algorithm

 AdaBoost is a boosting algorithm that constructs a classifier. This algorithm is relatively straightforward to program. 

AdaBoost Algorithm

SVMs are mainly used for learning classification, regression, or ranking functions. It is formed based on structural risk minimization and statistical learning theory

Support vector machines Algorithm

This is widely used to find the frequent itemsets from a transaction data set and derive association rules. Once we get the frequent itemsets,

Apriori Algorithm

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