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Add Advanced Data Mining Algorithms and Forecasting Functionality With IMSL
Whether forecasting future expenses, planning manufacturing production, predicting sales trends, or deriving an optimal trading strategy for securities, data mining and data forecasting can help organizations improve revenue, reduce costs, and mitigate risks.
Data mining algorithms help create valuable functionality for analytic applications. IMSL includes algorithms for regression analysis and chi-squared, plus advanced data mining techniques like genetic algorithms.
With data forecasting algorithms that range from correlation analysis to Naïve Bayes classification, IMSL data forecasting algorithms help organizations to create fast and accurate data forecasting applications.
IMSL data mining algorithms like the genetic algorithm, or the Naïve Bayes algorithm can help companies gain insights from large bodies of data in order to create high-ROI strategies.
A genetic algorithm can provide valuable functionality for many data mining applications. For example, by identifying the best indicators that will determine if a credit card applicant will be a credit risk, or by identifying patterns in purchase behavior to enable companies to better target price discounts.
As most organizations today have more text and documents than humans can keep track of, text mining is becoming an increasingly popular data mining and forecasting tool. With the IMSL C Library Naïve Bayes text mining algorithm, developers can create applications that search websites or customer relationship management system notes for timely and relevant data.
Accurate and timely forecasting and predictions can mean a huge competitive edge for companies. IMSL includes advanced forecasting techniques like Auto_ARIMA and Neural Network to help companies create applications with highly effective forecasting functionality.
The IMSL Library function, Auto_ARIMA, is an advanced forecasting routine for time series analysis with an ARIMA model.
With the Auto_ARIMA function, companies can create applications for sales forecasting, commodity pricing (e.g. oil & gas), stock market predictions, semiconductor yield analysis, and more.
Neural network forecasting and classification functions help users discover relationships and valuable information in vast amounts of data.
With a high degree of flexibility and control, the IMSL neural network forecasting and classification functions help companies in finance, business analytics, and bioinformatics create fast, effective analytic solutions.
To effectively address data mining and forecasting challenges, analysts need flexible, scalable, and reliable analysis tools. The IMSL Numerical Libraries, available in C, Java, Fortran, and Python, offer a proven, high-ROI solution for data mining, forecasting, and advanced predictive analysis applications.
Tested and proven over 50 years, IMSL libraries are trusted by major companies around the world.
Developing algorithms in house is expensive. Quickly integrate IMSL and avoid the extra cost.
With libraries in C, Fortran, Python, and Java, IMSL can be quickly integrated in your language of choice.
See how IMSL can add data mining and forecasting functionality to your application with a free trial.
Get an overview of the IMSL libraries with our datasheet.
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