Top Data Mining teaching Case Library (TIPDM-C10) Product white Paper

Top Data Mining teaching case Library

(TIPDM-C10)

Product Manual

Guangzhou Teddy Intelligent Technology Co., Ltd All rights reserved

Address: Guangzhou Economic and Technological Development Zone, No. No. 232

Website: http://www.tipdm.com

Email: [Email protected]

Hotline: 40068-40020

Enterprise qq:40068-40020

P.C.: 510663

Tel: (020) 82039399

Directory

1 overview ..... ..... ..... ..... .........-.......-........... ..... ..... ..... ..... ..... .............. .......... ............. 3

2 product composition ..... ..... ..... ..... ...................... ..... ..... ..... ..... ..... .............. .......... ........ 5

2.1 Case Technical Solution Book ..... ..... ......................... ..... ..... ..... ..... .............. ........... 5

2.2 Matching data files ..... ..... ..... ..... ..................... ..... ..... ..... ..... ..... ............. .......... 5

2.3 Supporting use Case program ..... ..... ..... ..... .................... ..... ..... ..... ..... ..... ............. .......... 6

3 Contact us ...... ..... ........................... ..... ..... ..... ..... ..... .............. .......... ........ 8

1 overview

The top data Mining teaching case base (also known as 10 selected data mining cases and practice drills, TIPDM-C10, abbreviated as C10) is Teddy technology in the field of data mining for more than 10 years and senior lecturer of the joint experience summary of the work, covering telecommunications, electricity, manufacturing, Internet, banking, aquatic products, Tax and many other industries, especially suitable for the teaching of data mining related courses in universities, research institutes and training institutions, but also as a personal learning data mining technology best material.

10 featured data mining cases include:

1) automatic identification of electric power stealing leakage users

Case Description: Through the acquisition of electric power metering automation system, such as current, voltage, power factor, such as electricity load data, electrical anomalies and other terminal alarm information and power marketing system to provide the history of the leakage of the use case, summed up the key characteristics of the leakage users, build a user identification model of leakage, and finally through monitoring user power data, To realize the real-time online diagnosis of leakage users.

Practical Walkthrough Environment: MATLAB, SAS, SPSS, R

2) Airline Customer value analysis

Case Description: Fierce market competition, each airline has introduced a more preferential marketing methods to attract more customers, domestic airlines are mostly faced with frequent traveller loss, competitiveness decline, aviation resources are not fully utilized and other business crisis. Through the establishment of a reasonable customer value assessment model, customer clustering, analysis and comparison of different customer groups of customer value, and to formulate corresponding marketing strategies, to different customer groups to provide personalized customer service.

Practical Walkthrough Environment: MATLAB, SAS, SPSS, R

3) Mining Association Rules of TCM syndrome type

Case Description: With the help of the pathological information of the patients with tri-yin breast cancer, it is found that the relationship between TCM symptoms and the regularity of many symptoms, mining latent syndrome, and according to rules analysis etiology, predict the disease development and provide effective reference for the future clinical diagnosis and treatment. In this way, the doctor can effectively reduce the toxic side effects of Western medicine and chemotherapy, and lay the foundation for the follow-up treatment.

Practical Walkthrough Environment: MATLAB, SAS, SPSS, R

4) Water quality evaluation based on Aqua image

Case description: As water can reflect the type and number of phytoplankton in the aquatic species, the water quality can be regulated by observing the change of color, so as to maintain a reasonable dynamic balance of phytoplankton, microorganisms and zooplankton in the aquatic ecosystem. Based on the experience of historical aquatic experts and the data collected by the digital camera according to the standard, the paper uses image processing technology to realize water quality automatic evaluation on the basis of aqua image.

Practical Walkthrough Environment: MATLAB, SAS, SPSS, R

5) Application System load analysis and disk capacity prediction

Case Description: Any resource that is associated with an application is too heavy to cause system performance to degrade or even be paralyzed. By analyzing disk capacity-related data, the application system server disk space is forecasted to meet the requirements of healthy system operation. According to the user needs to set different warning level, the predicted value and capacity value comparison, the results of the early warning, to provide system administrators with customized warning prompt.

Practical Walkthrough Environment: MATLAB, SAS, SPSS, R

6) Relevance degree analysis for network public opinion

Case Description: The influence of network public opinion on political life order and social stability is increasing day by day, and some major network public opinion events make people realize the great effect of network on social supervision. By collecting the network public opinion information and analyzing object information from the community website, the paper establishes the calculating rules of the correlation degree between the analysis object and public opinion resource, and finds the analysis object which is closely related to the given public opinion resources.

Practical Walkthrough Environment: MATLAB, SAS, SPSS, R

7) Consumer behavior analysis and event recognition

Case Description: The use of household appliances in the process, due to regional climate, regional differences, user age and gender differences, the formation of different unit use behavior, called the user's usage habits. Based on the user's use of the water heater to build a bathing event recognition model, and then in-depth understanding of the water heater in the user's area of the real use habits, optimize the design of new products and layout marketing.

Practical Walkthrough Environment: MATLAB, SAS, SPSS, R

8) Business Circle analysis based on base station location data

Case Description: The business district is the space of the enterprise market activity in the modern market, also is the area of the goods and the service consumer. One of the aims of the division of Commercial districts is to study the distribution of potential customers in order to formulate appropriate business strategies. From the base station location data provided by the communication operators, using the coverage range of the base station cell as the division of the area of the business district, the characteristics and laws of the pedestrian flow are summed up, and the different types of business districts are identified, and the marketing guidance is realized.

Practical Walkthrough Environment: MATLAB, SAS, SPSS, R

9) correlation analysis of meteorological and power transmission line defects

Case Description: Because most of the components of the transmission line are exposed, extreme weather conditions cause great harm to the transmission line. By analyzing the relationship between the defects such as bird pest, grounding device damage, protected area safety hidden danger, component heating anomaly, corrosion damage and meteorological factors, this paper constructs an early warning model of the relationship between meteorological factors and defects. To realize the probability of defects occurring in the extreme weather conditions and to make early warning.

Practical Walkthrough Environment: MATLAB, SAS, SPSS, R

10) e-Commerce Intelligent Recommendation Service based on association rules

Case Description: According to the user access data collected by the e-commerce website, the user's access to the content of the association rules analysis, to explore the user access to the website business logic relationship, for users to recommend accurate knowledge content and services, so as to establish a stable site loyal customer base, to achieve customer chain reaction value-added, For the enterprise to achieve more personalized customer positioning, improve consumer satisfaction.

Practical Walkthrough Environment: MATLAB, SAS, SPSS, R

More project examples see: www.tipdm.org

2 Case Product Composition

1. 1.
2. 2.
3. 3.

3.1.

2.1 Case Technical Solution Book

Case technical Manual by the Teddy Technology and a number of university teachers combined refining and refinement, in a brief introduction of a data mining application from the request to the final realization of the entire process, case technology book according to the following structure of the organization of Materials:

1. Background and excavation target

2. Analysis method and process

1) Data extraction

2) Data exploration

3) Data preprocessing

4) Model Building

5) Model evaluation

6) Model Application

3, on-machine experiment

4, expand thinking

Example:

2.2 Companion data files

Supporting data files mainly include source files, process files and result files, respectively, stored in the sample program, on-machine experiments, the expansion of computer experiments and expand thinking and other folders.

The following is the data file in the sample program:

The following are the data files in the computer lab:

2.3 Supporting use case programs

The use case procedure mainly includes the case procedure example procedure, the Computer Experiment Program (MATLAB environment), the Computer Experiment Expansion program (SPSS, SAS and R language).

The following is the MATLAB program in the sample program:

The following is the MATLAB program in the computer experiment:

The following is the SAS program in the expansion of the computer experiment:

The following is the SPSS model in the expansion of the computer experiment:

3 Contact Us

Thank you for choosing Guangzhou Teddy Technology Company's data mining products, in the system of the use of the process if you encounter problems, please contact us by the following means, we will provide users with thoughtful and satisfactory service.

Home : http://www.tipdm.com

Tel : 020-82039399

Fax : 020-28871586

Hotline : 40068-40020

Add : No. No. 232, Ke Zhu Road, science and technology zone, Guangzhou

P.C. : 510663

email : [email protected]

Top Data Mining teaching Case Library (TIPDM-C10) Product white Paper