A real estate evaluation method based on machine learning

Abstract

The invention relates to a real estate evaluation method based on machine learning, in particular to the following steps: (1) preparing in the early stage: adopting a distributed file system for storing large data, firstly deploying a large data storage system; (2) starting the evaluation process, comparing and analyzing the information between the real estate to be evaluated and the database through the big data analysis and data mining analysis technology to identify the characteristics of the real estate; (3) according to the characteristic system of the immovable property obtained in the step (2), automatically matching the evaluation methods to be used from a plurality of evaluation methods, selecting the evaluation methods, referring to the reference factors of the comparison data, and calculating and giving the final evaluation value according to the calculation formula; at the same time, the appraisal process will be completed after the real estate information and operation experience of the appraisal being stored in the learning achievement database and database. Based on computer machine learning, continuous learning, and accumulating the results of the database information, the reference factors of evaluation calculation are optimized, so that the evaluation results more scientific and objective.

Description

technical field [0001] The present invention relates to the technical field of machine learning, in particular to a real estate evaluation method based on machine learning. Background technique [0002] With the establishment and implementation of the real estate registration system, real estate, land, forestry, grassland, minerals, oceans and other resources have been unified into the scope of real estate and registered in the same "real estate registration system". People's awareness of property rights has gradually improved, and real estate transactions have become increasingly active, which has led to the rise of the real estate appraisal industry. [0003] The traditional real estate evaluation method is manually compared and estimated according to the relevant conditions. The reference factors are not comprehensive, greatly affected by subjective factors, time-consuming and labor-intensive, and cannot keep up with the speed of social and economic development. [0004]...

AI Technical Summary

Problems solved by technology

[0007] (1) The information is not comprehensive: the information held by the intermediary or evaluation company comes from the existing evaluation information of the intermediary company or evaluation company, and only represents part of the information on the location of the real estate

[0008] (2) Inaccurate information: the source of real estate value information and online intermediary information or offline contract information are not the real transaction value of real estate

[0009] (3) Low evaluation efficiency: Without the use of big data technology, traditional data storage and analysis methods, it is difficult to keep up with the rapid changes in real estate information

[0010] (4) Evaluation is unscientific: using general evaluation software or methods, the evaluation theory basis is immutable and has no self-improvement ability. It is a way to evaluate differentiated real estate in a way of "constant and adaptable to all changes", which is difficult to do accurately Evaluate

Among them, the historical data are incomplete, and the content may not be true and effective

And the reference factors are not comprehensive and objective

Evaluation is inefficient and not very objective

There is no technical solution or invention patent similar to the patent of the present invention

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