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Introduction to Computer science data compression Basics (outline)

1. Introduction1 What is data compression?Data compression reduces the amount of data sent or stored by partially eliminating the inherent redundancy in the data.Data compression improves the efficiency of data transfer and storage, while protecting the integrity of the database.2

(Data Science Learning Codex 23) Decision tree Classification principle detailed &python and R implementation

arguments are missing samples (decision tree is more tolerant of missing values, there are corresponding processing methods)Parms: The default is the "Gini" index, which is the method of the CART decision tree Partition node;> Rm (list=ls ())>Library (Rpart.plot)>Library (Rpart)>data (Iris)> Data Iris> Sam 1: Max, -)> Train_data Data[sam,]> Test_data Sam,]> Dtre

[Turn] Hand Travel research data Professional terminology Popular science game What's the heat?

at all times. Based on this statistic, you'll see which upgrades are selling better and are more popular with players. Further down, you can also find out if a user is only involved in a certain type of micro-transaction and make adjustments (if necessary) to the game based on this.Finally, I hope the above list of indicators will help game developers to better study game performance. Keep in mind that specific indicators may only be available for specific games, and you need to select the corr

The complete learning Path of data science

you don't like the learning style of interactive coding, you can also learn Google's Python lessons. This 2-day course series contains not only the Python knowledge mentioned earlier, but also some of the things that will be discussed behind it. Step 3: Learn regular expressions in the Python language You will often use regular expressions to clean up data, especially when you are working with text data. T

An RDBMS summary of introduction to Data Science in public class

manual optimization in the homework similarity matrix, we need to calculate the similarity of 22 documents, which is actually a matrix operation. 1) The code is as follows, spents 1m22.042sSelect X.docid,y.docid,sum (X.count*y.count) as Count from Frequency X, Frequency y where x.term = Y.term and X.docid 2) Submit the answer only need, one of the results, time 1m10.919s, you can see here is actually calculated the similarity of all documents intercepted, DB is not optimized.SELECT * FROM (sele

Data Science Manual (R+python) reference information URL

:15px "> learning R Blog URL: http://learnr.wordpress.com p26_27 r home page: http://www.r-project.org rstdio home page:/http/ www.rstdio.com/ r Introduction: http://www.cyclismo.org/tutorial/R/ r a relatively complete getting Started Guide: http://www.statmethods.net/about/sitemap.html plyr Reference Document: Http://cran.r-projects.org/web/packages/plyr/plyr.pdf ggplot2 Reference Document: Http://cran.r-project.org/web/packages/ggplot2/gg

Pycharm+eclipse Shared Anaconda Data Science environment

the Pythonpath:spark installation directory4. Copy the Pyspark packageWrite Spark program, copy pyspark package, add code display functionIn order for us to have code hints and complete functionality when writing Spark programs in pycharm, we need to import the pyspark of spark into Python. In Spark's program, there's a python package called Pyspark.Pyspark BagPython is also easy to import third-party packages, just import the corresponding modules into the specified folder.Windows copies Pyspa

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