Big Data Analyzing Techniques in Mathematical House Price Prediction Model
Product Description
Aim:
As the house price prediction is vital for both the Ill-being of the public and the economic development, many experts in different research fields have explored and predicted it with the machine-learning strategies. Because the price is susceptible to multiple factors, it is very challenging to obtain the accurate number.
Abstract:
The Chinese house market has been flourishing in the past three decades as an increasingly bigger population moves into cities. To keep the rise of house price within a proper range and acceptable to the public, the government has adopted various approaches to bring the price under control. After intermittent fluctuations, house purchasing has become a hot topic for both the media and the public. It is of great significance to study the change of house price considering all the related factors. Some scientists prefer machine learning. Machine learning is a subject which involves many subjects such as probability theory, statistics, approximation theory, convex analysis, and algorithm complexity theory. In this paper, we will discuss the details of the machine learning algorithms and their strengths and weaknesses. In the future, the growing complexity of all the factors that influence house price will cause more and more trouble for scientists pursuing more precise results.
Proposed System:
The machine-learning strategies. The three main approaches which are popular in this field to predict prices are AdaBoost, Linear Regression and KNN. Because the price is susceptible to multiple factors, it is very challenging to obtain the accurate number.
Advantage:
Collect the related information, and transform them into data, so that scientists can use suitable models and algorithms to analyze and evaluate the results in an increasingly accurate way. It has become a hot and vital issue to develop more advanced models and algorithms, which scientists have been working on to overcome for decades.
When you order from finalyearprojects.in, you will receive a confirmation email. Once your order is shipped, you will be emailed the tracking information for your order's shipment. You can choose your preferred shipping method on the Order Information page during the checkout process.
The total time it takes to receive your order is shown below:
The total delivery time is calculated from the time your order is placed until the time it is delivered to you. Total delivery time is broken down into processing time and shipping time.
Processing time: The time it takes to prepare your item(s) to ship from our warehouse. This includes preparing your items, performing quality checks, and packing for shipment.
Shipping time: The time for your item(s) to tarvel from our warehouse to your destination.
Shipping from your local warehouse is significantly faster. Some charges may apply.
In addition, the transit time depends on where you're located and where your package comes from. If you want to know more information, please contact the customer service. We will settle your problem as soon as possible. Enjoy shopping!
Download Abstract
Click the below button to download the abstract.
Package Includes
Software Projects Includes
- Demo Video
- Abstract
- Base paper
- Full Project PPT
- UML Diagrams
- SRS
- Source Code
- Screen Shots
- Software Links
- Reference Papers
- Full Project Documentation
- Online support
The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days
Hardware Projects Includes
- Demo Video
- Abstract
- Base paper
- Full Project PPT
- Datasheets
- Circuit Diagrams
- Source Code
- Screen Shots & Photos
- Software Links
- Reference Papers
- Lit survey
- Full Project Documentation
- Online support
The Delivery time for Hardware
projects is 7-8 working days.
Mini Projects: Software Includes
- Demo Video
- Abstract
- Base paper
- Full Project PPT
- UML Diagrams
- SRS
- Source Code
- Screen Shots
- Software Links
- Reference Papers
- Full Project Documentation
- Online support
The
Delivery time for software Miniprojects is 2 -3 working days.
Mini Projects - Hardware includes
- Demo Video
- Abstract
- PPT
- Datasheets
- Circuit Diagrams
- Source Code
- Screen Shots & Photos
- Software Links
- Reference Papers
- Full Project Documentation
- Online
support
The Delivery time for Hardware Mini projects is 7-8 working days.