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{ "item_title" : "Feature Projection in Machine Learning", "item_author" : [" Landa Tejeswara Rao", "Karakavalasa Durga Akhil "], "item_description" : "Random projection is a well-known AI calculation, which can be executed by neural organizations and trained in an effective way. Adaptive Regularize Parameter Selection it will regularize the features which are important and select a most suitable feature for a specific problem. The main goal is to reduce the computational cost of both classification and regression task by using Randomization Algorithm. It provides the best possible result to the high-dimensional optimization. It uses Multi layer neural network for performing linear and non linear function.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/9/79/850/581/9798505814994_b.jpg", "price_data" : { "retail_price" : "12.00", "online_price" : "12.00", "our_price" : "12.00", "club_price" : "12.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Feature Projection in Machine Learning|Landa Tejeswara Rao

Feature Projection in Machine Learning : Artificial Intelligence

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Overview

Random projection is a well-known AI calculation, which can be executed by neural organizations and trained in an effective way. Adaptive Regularize Parameter Selection it will regularize the features which are important and select a most suitable feature for a specific problem. The main goal is to reduce the computational cost of both classification and regression task by using Randomization Algorithm. It provides the best possible result to the high-dimensional optimization. It uses Multi layer neural network for performing linear and non linear function.

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Details

  • ISBN-13: 9798505814994
  • ISBN-10: 9798505814994
  • Publisher: Independently Published
  • Publish Date: May 2021
  • Dimensions: 9.02 x 5.98 x 0.18 inches
  • Shipping Weight: 0.28 pounds
  • Page Count: 88

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