Moreover, they present a business decision-making context for these methods and use real business cases and data to illustrate the application and interpretation of these methods.
These resources will give you both a theoretical and practical understanding of the key methods of classification, prediction, reduction and exploration that are at the heart of data mining.
This book, written by three data mining experts and published by Wiley, includes concepts, techniques, and applications in Excel using Analytic Solver Data Mining.
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Powerful data exploration and visualization features, in additional to its data preparation, data mining, and time series forecasting methods.Easily use each model to forecast future values.Fit a range of models including exponential smoothing, ARIMA, and standard and seasonal models.Analyze time series data using ACF/PACF plots and smoothing techniques.Use both classical methods like MLR and logistic regression, and data mining methods like CART and neural networks, and compare their predictive powerīuilt in time series analysis tools including:.Use a range of supervised and unsupervised learning techniques for continuous and categorical data.Use visualization aids from simple bar, line and histogram charts to multiple linked charts, one-click changes to axes, colors and panels, zooming, brushing and more.Powerful tools for analysis and prediction including: Partition your data into training, validation, and test datasets.Clean your data with a comprehensive set of data handling utilities including categorizing data and handling missing values.