Liver disease prediction using SVM algorithm in python

 

Liver disease prediction using SVM algorithm

 

 PROJECT ID: PYTHON15

 

PROJECT NAME: Liver disease prediction using SVM algorithm

 

PROJECT CATEGORY: MCA / BCA / BCCA / MCM / POLY / ENGINEERING

 

PROJECT ABSTRACT:

In this study, the liver disease data were collected from the UCI Machine learning repository [8]. The dataset contains 583 records with 11 features including Age, Gender, TB, DB, Alkphos, Sgpt, Sgot, TP, ALB, A/G ratio, and target label. Table 1 provides a detailed description and the type of features [9]. The dataset was split into two sets that included 416 records for group 1(liver patients) and 167 records for group 2(non-liver patients).

SOFTWARE REQUIREMENTS:

OS                                : Windows

Python IDE                  : Python 2.7.x and above

Language                             : Python Programming

Database                             : MYSQL

 

HARDWARE REQUIREMENTS:

 RAM                :  4GB and Higher

Processor          :  Intel i3 and above

Hard Disk         : 500GB Minimum

 

Data Mining

Applying data mining models in medical research such as for Liver Disease is a significant undertaking because of the large volumes of available Liver-related datasets for extracting knowledge. Hence, it is necessary to provide a general schema of data mining by presenting a tree structure. Fig. 3 shows medical data mining models [10]. Data mining methods are mainly divided into two categories: descriptive and predictive methods.

Descriptive methods

These methods find descriptive patterns that explain the data-based relationships regardless of any labels or output variables, i.e. the decision variable is unknown in descriptive methods. Clustering [11,12], association rule mining [13,14], and sequential pattern discovery [15] are three methods of model learning with a descriptive nature in data mining.

TABLE OF CONTENTS

·        Title Page      

·        Declaration

·        Certification Page

·        Dedication

·        Acknowledgements

·        Table of Contents

·        List of Tables

·        Abstract

 

CHAPTER SCHEME

CHAPTER ONE: INTRODUCTION

CHAPTER TWO: OBJECTIVES

CHAPTER THREE: PRELIMINARY SYSTEM ANALYSIS

·         Preliminary Investigation

·         Present System in Use

·         Flaws In Present System

·         Need Of New System

·         Feasibility Study

·         Project  Category

CHAPTER FOUR: SOFTWARE ENGINEERING AND PARADIGM APPLIED   

·         Modules

·         System / Module Chart

CHAPTER FIVE: SOFTWARE AND HARDWARE REQUIREMENT

CHAPTER SIX: DETAIL SYSTEM ANALYSIS

·         Data Flow Diagram

·         Number of modules and Process Logic

·         Data Structures  and Tables

·         Entity- Relationship Diagram

·         System Design

·         Form Design 

·         Source Code

·         Input Screen and Output Screen

CHAPTER SEVEN: TESTING AND VALIDATION CHECK

CHAPTER EIGHT: SYSTEM SECURITY MEASURES

CHAPTER NINE: IMPLEMENTATION, EVALUATION & MAINTENANCE

CHAPTER TEN: FUTURE SCOPE OF THE PROJECT

CHAPTER ELEVEN: SUGGESTION AND CONCLUSION

CHAPTER TWELE: BIBLIOGRAPHY& REFERENCES          

Other Information

 

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PROJECT WITH HARD BINDING	1850/- Only
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