You get a bonus - 1 coin for daily activity. Now you have 1 coin

6 Search for associative rules - Rules Mining

Lecture



Completed task. Reviewed forms for presenting results
(classification rules, classification tree, mathematical functions), method
di construction of classification rules (algorithm for constructing rules, method
Naive Bayes), as well as methods for constructing classification trees (
"divide and conquer" (algorithm of coverage), methods for constructing mathematical
functions (general form, linear methods, least squares method, non-
linear methods, support vector machines (svm), regularization networks
(Regularization Networks), discretization and sparse grids). considered by resolution
new task of searching for associative rules (formal formulation of the problem,
sequential analysis, types of problems of search for associative rules),
algorithms (Apriori algorithm, a kind of Apriori algorithm).

PLAN

1 Statement of the problem.
2 Presentation of results (classification rules, classification tree,
math functions).
3 Methods for constructing classification rules (algorithm for constructing rules
fork, Naive Bayes method).
4 Methods for constructing classification trees (divide and pas
Nui ", coverage algorithm).
5 Methods for constructing mathematical functions (general form, linear
methods, least squares method, nonlinear methods, Support Vector
Machines (SVM), Regularization Networks (Regularization Networks), Discrimination
cretizations and rare nets).
6 Statement of the problem of search for associative rules (formal
task setting, sequential analysis, variety of the problem of asociation search
rules).
7 Presentation of results.
8 Algorithms (algorithm Apriori, variations of the algorithm Apriori).
Literature: basic [1; 2; 3; four]; additional [10; 13; 14; 15].


Comments


To leave a comment
If you have any suggestion, idea, thanks or comment, feel free to write. We really value feedback and are glad to hear your opinion.
To reply

Data mining

Terms: Data mining