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Categories

Computer Science

Data Mining

Association Rule Learning

Anomaly Detection Methods

Big Data Technologies

Clustering Algorithms

Classification Algorithms

Data Dimensionality Reduction Techniques

Data Mining Project Lifecycle

Data Mining Success Metrics

Data Mining Techniques

Data Mining and Customer Relationship Management (CRM)

Data Mining for Fraud Detection

Data Mining in Finance

Data Quality Issues

Data Mining in Retail

Data Mining in Healthcare

Data Mining Research Topics

Data Mining Tools and Software

Data Mining Skill Set

Data Mining Case Studies

Data Preprocessing Techniques

Data Mining Challenges

Ensuring Data Privacy in Data Mining

Ethical Aspects of Data Mining

Frequent Pattern Mining Algorithms

Machine Learning vs Data Mining

Mining Complex Data Types

Multimedia Data Mining

Predictive Analytics Fundamentals

Time Series Analysis in Data Mining

Web Mining Methods

Social Media Data Mining

Spatial Data Mining

Text Mining Techniques

Predictive Analytics Fundamentals

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Clustering

Clustering is the task of grouping a set of objects in such a way that objects in the same group, called a cluster, are more similar to each other than to those in other groups. In data mining, it's used to discover structure within unlabeled data.

Regression

Regression analysis predicts a continuous numeric outcome. In predictive analytics, regression models predict the value of a variable based on other input variables.

Association Rule Learning

Association rule learning finds interesting associations and relationships among large sets of data items. This technique is used in market basket analysis to discover rules that indicate the items that frequently co-occur in transactions.

Support Vector Machine (SVM)

Support Vector Machine (SVM) is a supervised machine learning algorithm which can be used for both classification or regression challenges. In predictive analytics, it is mostly used for classification problems and works well on both linear and non-linear data.

Classification

Classification is the process of predicting the category or class of a given data point. In predictive analytics within data mining, classification algorithms are used to assign categories to data instances based on training data.

Time Series Analysis

Time Series Analysis involves methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Predictive analytics use it to forecast future events based on observed temporal sequences.

Decision Trees

A Decision Tree is a flowchart-like tree structure where an internal node represents a feature(or attribute), a branch represents a decision rule, and each leaf node represents the outcome. It is used in predictive analytics for classification problems to derive a strategy to reach a particular goal.

Ensemble Methods

Ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. It is used in predictive analytics to combine the strengths of different models.

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