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{ "item_title" : "Machine Learning and Data Mining", "item_author" : [" Carlton Braganza "], "item_description" : "The book Machine Learning and Data Mining focuses on different classification techniques, such as decision trees, support vector machines, and nearest neighbors. It delves into methods like decision trees, support vector machines, and nearest neighbors. The book offers a comparative analysis of these algorithms, emphasizing their individual advantages and drawbacks. Its aim is to assist researchers, practitioners, and data scientists in selecting the most appropriate classification algorithm for their particular requirements. By providing insights into the different techniques, this comprehensive guide aids in the decision-making process when it comes to choosing the right approach for classification tasks. This comprehensive guide helps researchers, practitioners, and data scientists choose the most suitable classification algorithm for their specific needs.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/8/11/936/563/8119365631_b.jpg", "price_data" : { "retail_price" : "149.99", "online_price" : "149.99", "our_price" : "149.99", "club_price" : "149.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Machine Learning and Data Mining|Carlton Braganza

Machine Learning and Data Mining

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Overview

The book "Machine Learning and Data Mining" focuses on different classification techniques, such as decision trees, support vector machines, and nearest neighbors. It delves into methods like decision trees, support vector machines, and nearest neighbors. The book offers a comparative analysis of these algorithms, emphasizing their individual advantages and drawbacks. Its aim is to assist researchers, practitioners, and data scientists in selecting the most appropriate classification algorithm for their particular requirements. By providing insights into the different techniques, this comprehensive guide aids in the decision-making process when it comes to choosing the right approach for classification tasks. This comprehensive guide helps researchers, practitioners, and data scientists choose the most suitable classification algorithm for their specific needs.

This item is Non-Returnable

Details

  • ISBN-13: 9788119365630
  • ISBN-10: 8119365631
  • Publisher: Discovery Publishing House (India)
  • Publish Date: April 2024
  • Dimensions: 9.61 x 6.69 x 0.63 inches
  • Shipping Weight: 1.4 pounds
  • Page Count: 272

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