data mining with rattle and r

Database/Data Mining/content retrieval International academic journal recommended by China Computer Society(Database/Data mining/content Retrieval) One, category A serial number of publications referred to the full name of publishing house Web site 1 TODS ACM Transactions on Database Systems Acm http://dblp.uni-trier.d

Operating system: Windowspython:3.5Welcome to join the Learning Exchange QQ Group: 657341423 The previous section describes the library of data analysis and mining needs, the most important of which is pandas,matplotlib.Pandas: Mainly on data analysis, calculation and statistics, such as the average, square bad.Matplotlib: The main combination of pandas to genera

Model:----Vmap=arg Max P (Vj | a1,a2...an)VJ belongs to the V collectionThe Vmap is the most probable target value given by a example.The a1...an is the attribute within this example.In this, the Vmap target value is the one that is the most likely to be calculated later. So with Max.----The Bayesian formula is applied to P (Vj | a1,a2...an).Can get vmap= arg max P (a1,a2...an | VJ) P (VJ)/P (a1,a2...an)And because naive Bayesian classifier defaults a1...an them to each other independently.So P

One, unsupervised learning1. Clustering: It is a process of classifying and organizing data members with similar data concentrations in some aspects. Therefore, a cluster is a collection of some data instances. Clustering techniques are often called unsupervised learning.Second, K-means clustering1, K-means algorithm: is the discovery of a given dataset K cluster

Model:----Vmap=arg Max P (Vj | a1,a2...an)VJ belongs to the V collectionThe Vmap is the most probable target value given by a example.The a1...an is the attribute within this example.In this, the Vmap target value is the one that is the most likely to be calculated later. So with Max.----The Bayesian formula is applied to P (Vj | a1,a2...an).Can get vmap= arg max P (a1,a2...an | VJ) P (VJ)/P (a1,a2...an)And because naive Bayesian classifier defaults a1...an them to each other independently.So P

with SQL. The database tables are then collated and pasted. Ubuntu unstable ah, the crash twice. The editor's blog is gone. Tired sleep does not love.Personal questionsThe disadvantage mentioned above is that the effect of the AdaBoost algorithm relies on the selection of weak classifiers, so how to choose the weak classification in the face of huge data to be classified? There are no principles. Bloggers are still exploring and finding answers will

　　 Data mining makes proactive, knowledge-based decisions by predicting future trends and behaviors. The goal of data mining is to discover the hidden and meaningful knowledge from the database, which mainly has the following five kinds of functions. 1. Automatically predict trends and behaviors

1.c4.5 algorithm2. K-mean-value clustering algorithm3. Support Vector Machine4. Apriori Correlation algorithm5.EM maximum expectation algorithm expectation maximization6. PageRank algorithm7. AdaBoost Iterative algorithm8. KNN algorithm9. Naive Bayesian algorithm10, CART classification algorithm.1.c4.5 algorithmWhat does C4.5 do? C4.5 constructs a classifier in the form of a decision tree. To do this, you need to give a collection of data that has bee

Data Mining (DW) is a very important part of business intelligence (BI) all week. What is the data mining in the end, this article will explore this. People often encounter this situation in their daily lives: supermarket operators want to be often bought together by the goods in order to increase sales; Insurance com

Content recommendationNew Internet: Big Data Mining provides a comprehensive overview of how data mining technology can be used to extract and generate business knowledge from a wide variety of structures (databases) or unstructured (WEB) mass data. The author combs a variet

A bunch of online searches, and finally the links and differences between these concepts are summarized as follows: 1. Data mining: Mining is a very broad concept. It literally means digging up useful information from tons of data. This work bi (business intelligence) can be done,