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Wolfram Mathematica More about Mathematica ยป

 |  | 

Exploratory Data Analysis

Building on Mathematica's powerful language and analysis capabilities, Mathematica 6 adds integrated exploratory data analysis, allowing the latest clustering, binning, smoothing and proximity methods to become a routine part of any computation.
  • Cluster analysis for numerical, Boolean and string data, in arbitrary dimensions, and with arbitrary distance functions. »
  • 20 built-in general distance and dissimilarity measures. »
  • Efficient general nearest-neighbor proximity function in any number of dimensions. »
  • General moving average and other smoothing functions. »
  • Full integration with Mathematica data sources, data import and visualization.
Conveniently Compute Moving Averages
Immediately Perform Cluster Analysis
Find Strings Nearest in Edit Distance
Find Nearest Neighbors in Any Space
 
Related Functions
FindClusters  BinCounts  BinLists  Tally  MovingAverage  MovingMedian
 
More About
Exploratory Data Analysis in Mathematica
Importing & Exporting Data
Partitioning Data into Clusters
Distance and Dissimilarity Measures
Basic Statistics
Data Transforms and Smoothing
New in 6.0: Data Handling & Data Sources
 
See Also New In 6.0
Language for Data Integration
Symbolic Statistical Computing
High-Impact Adaptive Visualization
Load-on-Demand Curated Data
Extended Array Operations
Integrated Geometric Computing



 
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