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Classification methods
Statistics and Machine Learning are Shih's allies to discover knowledge
Shih focuses on predictive modeling through the software Shih Data Miner, shortly know as Shih. Shih builds
models in an easy way.
Shih runs on any platform, it's simple and is addressed to the end user, not necessarily a statistician.
Shih can be used in diverse areas such as marketing, credit risk, insurance risk,
finance, medical diagnosis, pharmaceutical and scientific research.
Shih can be used to predict the risk outcome of bank operations,
such as credit cards approval, or the risk of existing loans,
through behavioural models.
In insurance companies Shih can assess
the risk of a client. In broker companies it can be used to do technical analysis
to predict the future tendency of a stock based on technical information.
In telephone companies it predicts which clients are likely to stay or leave.
In marketing it is used to segment and profile databases.
In the medical field Shih is used for diagnosis and illness prediction.
Feel free to evaluate Shih with your own data or with the sample data files.
Learn about prediction with Classification methods
Shih data miner
Shih data miner can be used in credit risk, prediction and forecast models,
market profilers, medical diagnosis, and pharmaceutical or scientific research.
It can be applied in diverse areas such as :
1) Risk management in banks to assess risk (credit/behaviour scoring) for credit cards, mortgage, small loans,
and fraud detection.
2) Medical applications, cancer prediction, diagnosis, and pharmaceutical research.
3) Communications, telephone companies or Internet service providers to avoid loosing customers
(churn scores), The tools are customized and can be applied in any area where prediction is an issue.
What we can do for you
We support our users because they test and extend the software constantly with their feedback. We also offer consultancy and development projects where we :
1) Analyze your data
2) Build models with you
3) Teach you how to do it
4) Implement the models
5) Configure the software for your use
