Transformation of Nominal Features Into Numeric in Supervised Multi-Class Problems Based on the Weight of Evidence Parameter

doi 10.15439/2015f90
Full Text
Abstract

Available in full text

Date
Authors
Publisher

IEEE

Related search

Graph Based Multi-Class Semi-Supervised Learning Using Gaussian Process

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2006English

Discovering Differences and Similarities Among Species Based on Numeric Features of microRNAs

2019English

ASIC: Supervised Multi-Class Classification Using Adaptive Selection of Information Components

2007English

A Novel Semi-Supervised Classification Method Based on Class Certainty of Samples

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2018English

Multi-Learner Based Recursive Supervised Training

International Journal of Computational Intelligence and Applications
Theoretical Computer ScienceComputer Science ApplicationsSoftware
2006English

Screening of Tobacco's Effective Image Features Based on a Semi -Supervised Clustering

2016English

Remapping Nominal Features in the Second Language

English

Effect of Non-Image Features on Recognition of Handwritten Alpha-Numeric Characters

INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY
2014English

Wordform- And Class-Based Prediction of the Components of German Nominal Compounds in an AAC System

2002English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy