data mining mooc

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[MOOC Notes] Chapter 1 Introduction (data structure)

, Are equivalent toBasic commands. In the progressive sense, the two are roughly the same. The main method for complexity analysis: 1. iteration: Sum of Series 2. recursion: recursive tracking + recursive equation 3. Prediction + Verification Level complexity: Arithmetic series Same level as last square Power Series Level 1 higher than power Geometric Series Same level as last Convergence level O (1) Geometric Distribution O (1)

JavaScript data type and type detection functions-MOOC ArraysSimilar programming exercises

JavaScript data type and type detection functions-MOOC ArraysSimilar programming exercisesBasic Type stringNumberBooleanFunctionUndefinedObject (null, Array, Date, window) implicit conversion with "=" num-string var str = num + ''string-num var num = str-0"=" For implicit conversion and determination (that is, to determine the value in the variable)"=" Directly determines (whether it is a thing) (NaN! = NaN

[MOOC notes] Chapter III list (data structure)

the tail node while (next = NODE.GETSUCC ())! = This.trailer) {//delete each of the same nodes if (Node.getdate (). Equals (Next.getdate ())) {This.remove (next);} else {node = next;}} Returns the scale change amount of return oldsize-this.size;}But because lists are seek location access rather than rank-and-seek access, an ordered list does not produce more efficiency in the lookup. Therefore, the lookup time complexity of the sequence table is the same as the normal list O (n).Note: This less

Chinese University mooc-Chen, He Chinming-Data structure basic problem sets 03-1. Two-part method for finding the polynomial single

, giving the interval endpoints a and B sequentially in line 2nd. The topic guarantees that the polynomial has a unique single root within a given interval. output format: Outputs the root of the polynomial within the range in a row, exactly 2 digits after the decimal point. Input Sample: 3-1-3 1-0.5 0.5 Output example: 0.33 Chinese University mooc-Chen, He Chinming-Data structure basic pr

Chinese University mooc-data Structure basic problem sets, 07-1, sorting

title Link:http://www.patest.cn/contests/mooc-ds/07-1Title Analysis: This two parts in the test of various different sorting algorithms in various data situations performance. Therefore there is no standard answer. The purpose of this post is to give the C + + implementation form of various sorting algorithms, and compare and summarize the results. Hope to bring you help . Code for various sorting algorithm

Frequent patterns mining (frequent pattern Mining) _ Data Mining

Frequent patterns mining (frequent pattern Mining) is a kind of mining commonly used in data mining, which is a frequent pattern mining algorithm called Apriori. First look at what is called frequent mode. ~ is the pattern that of

Use SharePreferences to access data (MOOC notes), sharepreferences

Use SharePreferences to access data (MOOC notes), sharepreferences 0. video address: http://www.imooc.com/video/3265 1. Use SharePreferences to access data: Public class MainActivity extends Activity {@ Override protected void onCreate (Bundle savedInstanceState) {super. onCreate (savedInstanceState); setContentView (R. layout. activity_main); SharedPreferences p

Log on to the instance and save the data (use SharedPreferences to save the user name for MOOC notes ).

Log on to the instance and save the data (use SharedPreferences to save the user name for MOOC notes ). Take notes when you perform operations after learning the video. 0. video address: http://www.imooc.com/video/3265 1. Function preview: Note: 1) enter the wrong user name and password and click log on. A prompt box is displayed, indicating "Logon prohibited "; 2) enter the correct user name and password,

An hour to understand data miningdata mining steps and common clustering, decision tree, and CRISP-DM concepts

An hour to understand data miningdata mining steps and common clustering, decision tree, and CRISP-DM conceptsNext Series 4:An hour to understand data mining ①: Resolving common Big Data

China University mooc-Chen, He Chinming-data structure-2015 Autumn 02-LINEAR structure 1

The product and sum of the two unary polynomials are obtained by the design function respectively.Input format:Input is divided into 2 lines, each line is given the number of non-0 polynomial, and then the exponential degradation way to enter a polynomial non-0 coefficients and exponents (absolute value is not more than 1000 integers). The numbers are separated by a space.Output format:The output is divided into 2 rows, and the coefficients and exponents of the product polynomial and the polynom

[MOOC Notes] sorting topics (data structure)

ordering.3. Merge sortIdea: Divide the whole sequence into multiple sub-sequences, sequence the subsequence sequentially, and finally merge into an ordered sequence, with the following algorithm:/** * Merge sort, time complexity O (NLOGN) * @param arr array to sort * @param the starting position of the lo to sort interval * @param hi to the end of the sort interval */public static void MergeSort ( Int[] arr, int lo, int hi) {//If there is only one element left in the interval, the recursive if

[Introduction to Data Mining]-Introduction to data types and Data Mining

[Introduction to Data Mining]-Introduction to data types and Data MiningData TypeDifferent datasets are manifested in many aspects. For example, attributes describing data objects can have different types: quantitative or qualitative. In addition, a dataset may also have a s

Data Mining (a) Do you really understand what is data mining and the data itself?

The idea of self-taught machine learning is really because of my interest in data mining, because in my heart I have always believed in the logic that there is a certain pattern behind everything, and that different situations only correspond to certain conditions. So to find such a pattern is the most convenient and quickest way to solve a class of problems, as a lazy person like me, of course, I would lik

[Introduction to Data Mining]-Introduction to Data Mining

[Introduction to Data Mining]-Introduction to Data MiningIntroduction to Data Mining Reading NotesPrerequisites for data mining: rapid advances in

Read "Data Mining Technology (third edition)"-Apply to marketing, sales and customer relationship management--data mining

Read "Data Mining Technology (third edition)"-Thoughts on marketing, sales and customer relationship management This book is not a purely data mining theory book, you can probably guess from the subtitle of this book. For a layman like me in the field of data

Python data analysis, R language and Data Mining | learning materials sharing 05, python Data Mining

Python data analysis, R language and Data Mining | learning materials sharing 05, python Data Mining Python Data Analysis Why python for data analysis? In terms of

Come with me. Data Mining (19)--What Is Data mining (2)

province to summarize sales data to view the Zhejiang-Shanghai area sales data. Slice (Slice): Select a specific value in the dimension for analysis, such as selecting only sales data for electronic products, or data for the second quarter of 2010. Cut (Dice): Select data f

Come with me. Data Mining (19)--What Is Data mining (2)

products, or data for the second quarter of 2010.Cut (Dice): Select data for a specific interval in a dimension or a specific value for analysis, such as sales data for the first quarter of 2010 through the second quarter of 2010, or for electronic products and commodities.rotation (Pivot): That is, the position of the dimension of the interchange, like a two-di

[Introduction to Data Mining]-quality of data quality and quality of Introduction to Data Mining

[Introduction to Data Mining]-quality of data quality and quality of Introduction to Data MiningData qualityThe data used by data mining is usually collected or collected for other purp

"Data Mining R Language Combat" book introduction, data Mining related people look over!

Today introduces a book, "Data Mining R language combat." Data mining technology is the most critical technology in the era of big data, its application fields and prospects are immeasurable. R is a very good statistical analysis and dat

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