Overview

A genetic disease or disorder is any disease that is caused by an abnormality in an individual's genome. The abnormality can range from minuscule to major -- from a discrete mutation in a single base in the DNA of a single gene to a gross chromosome abnormality involving the addition or subtraction of an entire chromosome or set of chromosomes.

1). Single gene inheritance -- Also called Mendelian or monogenic inheritance. This type of inheritance is caused by changes or mutations that occur in the DNA sequence of a single gene. T ....etc

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Genetic programming (GP) is an Automated Methodology

Genetic programming (GP) is an automated methodology inspired by biological evolution to find computer programs that best perform a user-defined task. It is therefore a particular machine learning technique that uses an evolutionary algorithm to optimize a population of computer programs according to a fitness landscape determined by a program's ability to perform a given computational task.

The first experiments with GP were reported by Steph ....etc

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1. INTRODUCTION

In this section we present genetic programming, being the fourth member of the evolutionary algorithm family. Besides the particular representation (using trees as chromosomes) it differs from other EA strands in its application area. While the EAs are typically applied to optimization problems, GP could be rather positioned in machine learning. In terms of nature of this deferent problem types, most other EAs are used for finding some input realizing maximum payoff, whereas GP is used to seek models with maximum fit. Clear ....etc

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Genetic programming has recently emerged as an important paradigm for automatic generation of computer programs. GP combines metaphors drawn from biological evolution with computer science techniques in order to produce algorithms and programs automatically.From the very beginning, man has tried to develop machines that can replace the need for human beings for many applications; machines that require very little support of human beings. Research is going on to develop machines that can produce high artificial components in the results, with le ....etc

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Abstract:
This paper presents an approach for integrating e-learning with the traditional education system. A conceptual map is then created for this integration leading to a functional model for open and flexible learning. In the proposed integration, convergence of CD-based, class based and web based education in recommended and architecture to achieve this convergence is presented. In order to transform the existing schools, colleges and universities into digital campuses, an inclusive system architecture is designed for digital campus. A c ....etc

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GENETIC PROGRAMMING A SEMINAR REPORT
Submitted by
GAURAV AHUJA
COMPUTER SCIENCE & ENGINEERING
SCHOOL OF ENGINEERING
COCHIN UNIVERSITYUNIVERSITY OF SCIENCE &
TECHNOLOGY, KOCHI-682022

ABSTRACT
Genetic programming (GP) is an automated methodology inspired by biological evolution to find computer programs that best perform a user- defined task. It is therefore a particular machine learning technique that use ....etc

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Genetic programming (GP) is an automated methodology inspired by biological evolution to find computer programs that best perform a user-defined task. It is therefore a particular machine learning technique that uses an evolutionary algorithm to optimize a population of computer programs according to a fitness landscape determined by a program's ability to perform a given computational task. The first experiments with GP were reported by Stephen F. Smith (1980) and Nichael L. Cramer (1985), as described in the famous book Genetic Programming: O ....etc

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Genetic programming (GP) is an automated methodology inspired by biological evolution to find computer programs that best perform a user-defined task. It is therefore a particular machine learning technique that uses an evolutionary algorithm to optimize a population of computer programs according to a fitness landscape determined by a program's ability to perform a given computational task. The first experiments with GP were reported by Stephen F. Smith (1980) and Nichael L. Cramer (1985), as described in the famous book Genetic Programming: O ....etc

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Abstract—In this paper, we present a novel framework, called learning by propagability, for two essential data mining tasks, i.e., classification and regression. The whole learning process is driven by the philosophy that the data labels and the optimal feature representation jointly constitute a harmonic system, where the data labels are invariant with respect to the propagation on the similarity graph constructed based on the optimal feature representation. Based on this philosophy, a unified framework of learning by propagability is propos ....etc

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Genetic programming (GP) is an automated methodology inspired by biological evolution to find computer programs that best perform a user-defined task. It is therefore a particular machine learning technique that uses an evolutionary algorithm to optimize a population of computer programs according to a fitness landscape determined by a program's ability to perform a given computational task. The first experiments with GP were reported by Stephen F. Smith (1980) and Nichael L. Cramer (1985), as described in the famous book Genetic Programming: O ....etc

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