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TRIP: An Interactive Retrieving Inferring Data Imputation Approach
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TRIP: An Interactive Retrieving - Inferring Data Imputation Approach

Category : Data Mining


Sub Category : JAVA


Project Code : ITJDM15


Project Abstract

TRIP: An Interactive Retrieving Inferring Data Imputation Approach

 

ABSTRACT

 

Existing imputation approaches to non-quantitive string data can be roughly put into two categories: (1) inferring-based approaches and (2) retrieving based approaches .Specifically, the inferring-based approaches find substitutes or estimations for the missing ones from the complete partof the data set. However, they typically fall short in fillingin unique missing attribute values which do not exist inthe complete part of the data set. In this project, we investigate the interaction between the inferring-basedmethods and the retrieving-based methods. We show that retrieving a small number of selected missing values can greatly improve the imputation recall of the inferring-based methods. With this intuition, we propose an inTeractive Retrieving-Inferring data imputation approach (TRIP), which performs retrieving and inferring alternately in filling in missing attribute values in a dataset. To ensure the high recall at the minimum cost, TRIP faces a challenge of selecting the least number of missing values for retrieving to maximize the number of inferable values.

 

 

EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING CONCEPT:-

Most existing imputation methods to string, attribute values are inferring-based approaches, which usually fail to reach a high imputation recall by just inferring missing values from the complete part of the data set

inferring-based approaches find substitutes or estimations for the missing ones from the complete part of the data set

PROPOSED CONCEPT: -

We proposed to retrieve and insert missing values from all kinds of web pages, which was proved to reach a higher imputation recall than the other approaches.

 For each blank in a data set, this general approach formulates proper imputation search queries to retrieve relevant web document.

EXISTING TECHNIQUE:-

Inferring-based approaches

PROPOSED TECHNIQUE:-

Retrieving-inferring based approaches

TECHNIQUE DEFINITION:-

Inferring-based imputation method often fails to fill in some missing values as not all missing values are inferable based on the inference rules corresponding to those constraints

TECHNIQUE DEFINITION:-

Retrieving-inferring based approaches  which retrieves and insert missing values from all kinds of data sets.

DRAWBACKS:-

Low imputation recall.

Will not retrieve data

 

ADVANTAGES:-

High imputation recall.

Both insert and retrieve data

 
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