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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

Classification Algorithms

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Support Vector Machine (SVM)

A discriminative classifier that finds an optimal hyperplane which maximizes the margin between different classes of data. Type: Supervised Learning Algorithm

Latent Dirichlet Allocation (LDA)

A generative statistical model that explains sets of observations as influenced by unobserved groups to discover hidden patterns in data. Commonly used in text data for topic discovery. Type: Unsupervised Learning Algorithm

Random Forest

An ensemble learning method that constructs multiple decision trees during training and outputs the mode of classes (classification) of individual trees. Type: Supervised Learning Algorithm

Gradient Boosting Machines (GBM)

An ensemble technique that builds additive models in a forward stage-wise fashion; it generalizes boosting methods by allowing optimization of an arbitrary differentiable loss function. Type: Supervised Learning Algorithm

Neural Networks

Consist of node layers, containing an input layer, one or more hidden layers, and an output layer where each neuron applies an activation function. Type: Supervised Learning Algorithm

K-Nearest Neighbors (KNN)

A non-parametric method used for classification and regression. A sample is classified by a majority vote of its neighbors, with the sample being assigned to the class most common among its k nearest neighbors. Type: Supervised Learning Algorithm

Naive Bayes Classifier

A probabilistic classifier based on applying Bayes' theorem with strong (naive) independence assumptions between the features. Type: Supervised Learning Algorithm

Decision Tree

A flowchart-like tree structure where internal nodes represent features, branches represent decisions, and each leaf node represents an outcome. Type: Supervised Learning Algorithm

Logistic Regression

A statistical model that uses a logistic function to model a binary dependent variable, although extensions exist for multiclass problems. Type: Supervised Learning Algorithm

AdaBoost

An ensemble technique that combines weak learners into a weighted sum that represents the final output of the boosted classifier. Type: Supervised Learning Algorithm

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