Research Article

A Parallel Attribute Reduction Method Based on Classification

Algorithm 3

Parallel attribute reduction algorithm.
(i)Input: decision table.
(ii)Output: A relative attribute reduction of decision table.
(iii)Stage 1:Find core attribute in parallel
(iv)Step 1: Each process assigns attributes as according to label and drawer principle, and meets.
(v)Step 2: Each process computes the core attribute in.
(vi)Step 3: Each process exchanges the core attribute with each other, and obtains the final core attribute..
(vii)Stage 2: Prejudge whether the core attribute is the result of reduction
(viii)
(ix) Stage 3. Step 1
(x)Stage 3: Attribute expansion stage
(xi)Step 1: Calculate the attributes to be added,.
(xii)Step 2: Each process assigns attributes as according to label and drawer principle, and meets the following condition .
(xiii)Step 3: Each process computes the best attributes to be added .
(xiv)Step 4: Each process sends the results of the calculations in Step3 to the main process..
(xv)Step 5: The main process receives calculation results of each process and calculates the attribute that is best to be added..
(xvi)Then main process distributes the results,.
(xvii)Step 6: Each process accepts the calculation results of the main process and updates the reduction results. ,;
(xviii)Step 7: If goto Stage4
(xix)else goto Stage 3. Step 2;
(xx)Stage 4:Attribute compression stage
(xxi)Step 1: Calculate the properties needed to be checked, .
(xxii)Step 2: Each process checks whether can be removed according to its. , send to main process
(xxiii)else Send -1 to main process.
(xxiv)Step 3: The main process receives the calculation result of the sub process, select one attribute to compress and distribute the results.
(xxv)Step 4: Each process updates the compression results ; ;
(xxvi)Step 5: return
(xxvii)else goto Stage 4.Step 2.