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Data Mining for Business Analytics Concepts, Techniques, and Applications in R, An Indian Adaptation 1st Edition By Shmueli, Bruce, Yahav, Patel, Lichtendahl, O P Wali

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eBook EPUB PDF Data Mining for Business Analytics Concepts, Techniques, and Applications in R, An Indian Adaptation 1st Edition By Shmueli, Bruce, Yahav, Patel, Lichtendahl, O P Wali ISBN-13: 978-9390421701 Data Mining ...

eBook EPUB PDF Data Mining for Business Analytics Concepts, Techniques, and Applications in R, An Indian Adaptation 1st Edition By Shmueli, Bruce, Yahav, Patel, Lichtendahl, O P Wali ISBN-13: 978-9390421701 Data Mining for Business Analytics: Concepts, Techniques, and Applications in R (An Indian Adaptation, 1st Edition) is an applied, resource-rich textbook that bridges statistical modeling with machine learning algorithms. Tailored by Professor O.P. Wali specifically for the South Asian academic and commercial landscape, this textbook teaches readers how to implement computational data mining scripts using the open-source R software environment to uncover hidden patterns and drive corporate decision-making. Core Overview & Practice Structure The curriculum is organized into seven core sections that guide students from data ingestion to real-world analytical case studies: • Preliminaries and Data Mining Process: Establishes the foundational workflow of data mining, data definitions, and initial steps for cleansing raw business metrics. • Exploration and Dimension Reduction: Focuses on initial data visualization strategies and mathematical dimension-reduction techniques like Principal Component Analysis (PCA) to make large datasets manageable. • Performance Evaluation: Instructs on how to mathematically assess the accuracy and reliability of predictive and classification models to avoid overfitting. • Prediction and Classification Methods: Explores the implementation of essential machine learning algorithms including linear regression, k-Nearest Neighbors (k-NN), Naive Bayes, classification/regression trees, logistic regression, neural networks, and ensembles. • Mining Relationships: Details unsupervised learning methods such as association rules, collaborative filtering for recommender systems, and cluster analysis. • Time Series Forecasting: Integrates econometric principles for forecasting business metrics using smoothing methods and ARIMA modeling. • Advanced Analytics & Case Studies: Highlights emerging modern methodologies including social network analysis and text mining, capped off by local business case studies.

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eBook EPUB PDF Data Mining for Business Analytics Concepts, Techniques, and Applications in R, An Indian Adaptation 1st Edition By Shmueli, Bruce, Yahav, Patel, Lichtendahl, O P Wali ISBN-13: 978-9390421701

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