Mathematica data analysis learn and explore the fundamentals of data analysis with the power of Mathematica
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| Format: | E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Birmingham, UK
PACKT Publishing
2015
Packt Publishing Packt Publishing, Limited Packt Publishing Limited |
| Ausgabe: | 1st ed. |
| Schlagworte: | |
| ISBN: | 9781785884450, 9781785884931, 178588445X, 178588493X |
| Online-Zugang: | Volltext |
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Inhaltsangabe:
- Title Page Preface Table of Contents 1. First Steps in Data Analysis 2. Broad Capabilities for Data Import 3. Creating an Interface for an External Program 4. Analyzing Data with the Help of Mathematica 5. Discovering the Advanced Capabilities of Time Series 6. Statistical Hypothesis Testing in Two Clicks 7. Predicting the Dataset Behavior 8. Rock-Paper-Scissors - Intelligent Processing of Datasets Index
- Hypotheses on true sample distribution -- Summary -- Chapter 7: Predicting the Dataset Behavior -- Classical predicting -- Image processing -- Probability automaton modelling -- Summary -- Chapter 8: Rock-Paper-Scissors - Intelligent Processing of Datasets -- Interface development in Mathematica -- Markov chains -- Creating a portable demonstration -- Summary -- Index
- Cover -- Copyright -- Credits -- About the Author -- About the Reviewer -- www.PacktPub.com -- Table of Contents -- Preface -- Chapter 1: First Steps in Data Analysis -- System installation -- Setting up the system -- The Mathematica front end and kernel -- Main features for writing expressions -- Summary -- Chapter 2: Broad Capabilities for Data Import -- Permissible data format for import -- Importing data in Mathematica -- Additional cleaning functions and data conversion -- Checkpoint 2.1 - time for some practice!!! -- Importing strings -- Importing data from Mathematica's notebooks -- Controlling data completeness -- Summary -- Chapter 3: Creating an Interface for an External Program -- Wolfram Symbolic Transfer Protocol -- Interface implementation with a program in С/С++ -- Calling Mathematica from C -- Interacting with .NET programs -- Interacting with Java -- Interacting with R -- Summary -- Chapter 4: Analyzing Data with the Help of Mathematica -- Data clustering -- Data classification -- Image recognition -- Recognizing faces -- Recognizing text information -- Recognizing barcodes -- Summary -- Chapter 5: Discovering the Advanced Capabilities of Time Series -- Time series in Mathematica -- Mathematica's information depository -- Process models of time series -- The moving average model -- The autoregressive process - AR -- The autoregression model - moving average (ARMA) -- The seasonal integrated autoregressive moving-average process - SARIMA -- Choosing the best time series process model -- Tests on stationarity, invertibility, autocorrelation, and seasonality -- Checking for stationarity -- Invertibility check -- Autocorrelation check -- Summary -- Chapter 6: Statistical Hypothesis Testing in Two Clicks -- Hypotheses about the mean -- Hypotheses about the variance -- Checking the degree of sample dependence
- Mathematica Data Analysis: Learn and explore the fundamentals of data analysis with power of Mathematica