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Data charm: data analysis based on open-source tools
Basic Information
Author: (US) yanert (janert, K. P .)
Translator: Huang Quan, Lu Changhui, Xu xuemei, Fei Liufeng
Press: Tsinghua University Press
ISBN: 9787302290988
Mounting time:
Published on: February 1, July 2012
Start: 16
Page number: 1
Version: 1-1
Category: Computer> Computer science theory and basic k
R
R (http://www.r-project.org) is used for statistical analysis and graphical computer language and analysis tools, in order to ensure performance, its core computing module is written in C, C ++ and FORTRAN. It also provides a scripting language (R) for ease of use. The r language is similar to the s language developed by Bell Labs. R supports a series of analysis technologies, including statistical testing, predictive modeling, and
Original Author: Chandan Goopta. [Chandan Goopta is a data research expert from the University of Kathmandu (Nepal Capital) dedicated to building intelligent algorithms for affective analysis. ]
original link:http://thenewstack.io/six-of-the-best-open-source-data-mining-tools/
In this day and age, it is no exaggeration to say that
In today's big data era, data is money. With the transition to an application-based domain, data shows exponential growth. However, 80% of the data is unstructured, so it requires a program and method to extract useful information and convert it into an understandable and available structured form.
A large number
Preface:
When talking about big data analysis tools, many people may not know what big data analysis tools are. At least most industries seldom mention big data analysis tools, big data
a cross-cutting area influenced by many disciplines, including database system, statistics, machine learning, visualization and information science, etc. data mining repeatedly using multiple data mining algorithms to determine patterns or reasonable models from observational data is a decision support process. By pre
1, RapidMiner
The tool is written in the Java language and provides advanced analysis techniques through a template-based framework. The biggest benefit of this tool is that users don't have to write any code. It is provided as a service rather than as a local software. It is worth mentioning that the tool topped the list of data mining tools.In addition to data mining, RapidMiner provides features su
numpy arrays and array-oriented computations.
3. Matplotlib
Matplotlib is a powerful data visualization tool and drawing library, is mainly used for plotting data diagram of the Python library, provides a variety of visual graphics to draw the command font, simple interface, you can easily grasp the format of the graphics, drawing all kinds of visual graphics.
M
architecture1) Data connectionSupports multiple data sources and supports multiple big data platforms2) Embedded one-stop data storage platformEthink embedded Hadoop,spark,hbase,impala and other big data platform, directly use3) Visuali
:
Powerful interactive shells (terminal and qt-based)
A browser-based notebook with support for code, text, mathematical expressions, inline plots and other rich media
Interactive data visualization and use of GUI toolkits
Flexible, embeddable interpreters to load into one ' s own projects
Performance tools for Parallel computing
Con
3. Large data processing capability
(1) Perfect fusion with ODPs, release its processing ability
(2) Support the operation and management of a single enterprise level 100,000 task
(3) Analysis tool supports the real time OLAP analysis of billion-level data
2. Product function
DPC provides full link data tool solutions for all, and everyone can find
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