tools used for data mining

of a certain attribute of a new data based on the massive historical data, combined with certain algorithms, and based on probability. Many data mining models, such as Bayesian, time series, and association rules, are common models. Different model algorithms can be applied based on different problem features. For exa

Ipython is a python interactive shellAnaconda, packaged toolbox, type Eclipse becomes j2ee,android, can be installed on its own, or it can be the next ready versionSymPy Powerful Symbolic Data toolBased on the NumPy library, scipy function library adds many library functions which are commonly used in mathematics, science and engineering calculation. Examples include linear algebra, numerical solutions for

only 1. So the count of conditional pattern bases is determined by the minimum count of nodes in the path.Depending on the conditional pattern base, we can get the conditional FP tree for that commodity, for example i5:According to the conditions of the FP tree, we can do a full array of combinations, to get the frequent patterns excavated (here to the commodity itself, such as i5 also counted in, each commodity mining out of the frequent pattern mus

from data warehouse is the biggest purpose of establishing data warehouse and using data mining. The essence and process of both are two things. In other words, data warehousing should be established first, and data

conclusions more precisely. Recently, a senior technical survey by Gartner group ranked data mining and artificial intelligence as "the top five key technologies that will have a profound impact on industry over the next 3-5 years", and has also ranked parallel processing systems and data mining as the top two of the

(' relative importance ') Plt.draw () plt.show () The code is a bit long, but mainly divided into two, one is model training, the other is based on the importance of training to screen important features and drawing. The attributes that are more important than 18 are obtained as shown in the following illustration: It is important to see the three properties of TILTLE_MR title_id gender. and the title related to the attributes are our analysis of the name, can be seen in some string propertie

To illustrate their relationship, we have to talk about business intelligence. From a technical point of view, the process of business intelligence is based on the data warehouse in the enterprise by the online analysis and processing tools, data mining tools, and the profes

First talk about the problem, do not know that everyone has such experience, anyway, I often met.Example 1, some websites send e-mails to me every few days, each e-mail content is something I do not interest at all, I am not very disturbed, to its abhorrence.Example 2, add a feature of a MSN robot, a few times a day suddenly pop out a window, recommend a bunch of things I don't want to know, annoying ah, I had to stop you.Every audience just want to see what he is interested in, rather than some

information system can actively explore the source of the information is not found in the hidden information, and to generate information through the user's knowledge.Data mining is a branch of computer science that involves extracting from large datasets. These processes combine the use of statistical methods and artificial intelligence. Data mining transforms

set from the data population. Tasks include: data source, data ing, data preparation evaluation, necessary data aggregation, and data sampling. 3. exploratory Data Analysis (

SQL (DMX) makes it easy for developers and DBAs to create data mining-related applications, in the past, they may only be familiar with creating database-related applications. Now, statements that use the data mining model for prediction are like join queries in SQL queries. That is, the first contact, using

often does not reflect the real world of universal characteristics.L Non-trivial: the so-called non-trivial, refers to the excavation of knowledge should be not simple, can not be similar to a famous sports commentator said "After my calculation, I found an interesting phenomenon, to the end of this game, the World Cup goal and the number of missed goals is the same." It was a coincidence! "That kind of knowledge. This seems to be needless to be explained, but many novice

Office 365 came out, this trend cannot be underestimated. · Attitude:Don't be afraid to handle large data volumes and complex processes in order to get results. Processing large datasets, data warehouses, and analysis sandboxes is critical to successful data mining.Data Mining not only produces technical results, but

Data With the development of database technology and the wide application of database management system, the amount of data stored in the database has increased dramatically, and there is a lot of data hiding behind it. Important information, if you can extract this information from the database, will create a lot of potential profits for the company, and this