This project aims to implement machine learning and data mining techniques for business intelligence using the Weka application. The dataset is analyzed using 10 different data mining techniques, and the performance is evaluated through practical assignments and visualizations. The clustering technique of K-means is implemented, and the data is visualized using classifiers. The dataset is also analyzed using content-based filtering and time series forecasting. The subject, course code, course name, and college/university are not mentioned.

SIT717 2019T2 Assignment 2: Technical Report

This is a technical report assignment for the course SIT717 Enterprise Business Intelligence. The assignment requires students to use data mining and machine learning methods to analyze a dataset and explore applications for business intelligence.

Desklib offers practical assignments and visualizations to learn machine learning and data mining for business intelligence.

Machine Learning and Data Mining for Business Intelligence | Desklib

Implementing Machine Learning and Data Mining Techniques for Business Intelligence

This project explores the applications of data mining and machine learning in business learning with the Weka software. It examines the health news dataset and covers practicals on data pre-processing, clustering algorithms, classification algorithms, and more.

Hartpury University and Hartpury College

Data Science and Big Data

Artificial Intelligence

Statistics and Probability

Enterprise Business Intelligence: Data Mining and Machine Learning Techniques

This activity explores the applications of data mining and machine learning for business intelligence using the health news dataset and Weka software. It covers topics such as clustering, classification, performance evaluation, time series prediction, text mining, and image analysis.

Utilizing Data Mining and Machine Learning for Business Intelligence

Practical

Desklib's Enterprise Business Intelligence project explores the applications of data mining and machine learning for business intelligence. The project analyzes the health news dataset using Weka data mining applications and is divided into 10 practicals covering topics such as clustering algorithms, supervised mining, performance evaluation, time series prediction, text mining, and image analytics. The project provides a step-by-step guide to installing Weka software, downloading the data repository, and data pre-processing. The project also includes data visualization and dimension reduction techniques.

Enterprise Business Intelligence: Data Mining and Machine Learning for Business Intelligence

This article discusses the implementation of K-Means Algorithm using Map reduce. It explains the steps involved in the algorithm and its effectiveness compared to the standard implementation. It also explores Weka implementation of K-Means algorithm. The article provides insights into the data set collection, K-Means Algorithm, Map Reduce, and the algorithm&#39;s implementation. The article is useful for data scientists, machine learning enthusiasts, and students.

K-Means Algorithm using Map reduce

Machine Learning Algorithms

This report provides an analysis of patients' responses on WEKA using data mining techniques such as classification and clustering. The report also discusses the advantages and disadvantages of using decision trees and Naive Bayes models for text analysis.

Implementing Machine Learning and Data Mining Techniques for Business Intelligence

Enterprise Business Intelligence: Data Mining and Machine Learning Techniques

Utilizing Data Mining and Machine Learning for Business Intelligence

Enterprise Business Intelligence: Data Mining and Machine Learning for Business Intelligence

K-Means Algorithm using Map reduce

Text Analysis on Patients’ Response on WEKA

ISY310 Business Analyses of Data Mining Report

Implementing Machine Learning and Data Mining Techniques for Business Intelligence

Enterprise Business Intelligence: Data Mining and Machine Learning Techniqueslg...

Utilizing Data Mining and Machine Learning for Business Intelligencelg...

Enterprise Business Intelligence: Data Mining and Machine Learning for Business Intelligencelg...

K-Means Algorithm using Map reducelg...

Text Analysis on Patients’ Response on WEKAlg...

ISY310 Business Analyses of Data Mining Reportlg...

Enterprise Business Intelligence: Data Mining and Machine Learning Techniques

Utilizing Data Mining and Machine Learning for Business Intelligence

Enterprise Business Intelligence: Data Mining and Machine Learning for Business Intelligence

K-Means Algorithm using Map reduce

Text Analysis on Patients’ Response on WEKA

ISY310 Business Analyses of Data Mining Report