数据挖掘的java算法

Compiling: CHC now requires the following sources from the cvs repository: mlj/src/chc mlj/src/id3 mlj/src/nb mlj/src/shared mlj/src/c45 Compile CHC from the src directory with the command listed below. javac chc/*.java Running: Run chc from the src directory with the following command java chc.CHCDriver [datafile] [options] Datafile: The data file to be tested with CHC. ie. vote, anneal, iris. CHC uses the datafile system {.names, .all, .data, .test, .train, .val} Make sure to include the path for the datafile if it is in another directory. Options: finalgeneration=# - CHC will terminate at the end of that generation - 1. populationsize=# - the maximum number of Hypothesisi spawned each generation. inducer=[inducer] - the inducer to be used when running chc. Options are naive, id3, c4.5. bitmask=[mask] - mask is a string of 7 bits. 1 indicating on; 0 indicatinf off; a description of the options controlled by the bitmask is below in the Printing Options section of this file in the order they appear. they correspond to the CHC Printing options of the MLJ-Options.file. Options can also be controlled from the MLJ-Options.file under the CHC options section finalgeneration # populationsize # inducer [inducer] FitnessDistribution #,#,# These are the same options as above. except FitnessDistribution which is used to implement the new outerloop fitness equation. The three numbers should all add to 1.0 and correspond to a, b, and c in the fitness equation. Log Options CHC uses the WRAPPER loglevel in the MLJ-Options.file. loglevel output 0 only basic errors 1 prints basic generational information. 2 print out the process of chc. 3 internal working of chc plus non basic errors 4 print whole population each generation 5-6 no change 7 debugging Inducers now run on the INDUCER loglevel in the MLJ-Options.file and the CatTestResults uses the CTR. If you are getting unwanted results try setting these loglevels to 0. Printing Options They are in the MLJ-Options file. print_all_hypothesis: prints all the hypothesesi created durring this run. best_overall_hypotheses: prints the top ten hypotheses average_fitness_per_generation: prints the average fitness per generation best_Spawned_Hypothesis_of_generation: prints the information of the best individual spawned in each generation best_overall_Hypothesis_of_generation: will print the information of the best overall Hypothesis to this point in the data run best_fitness_of_each_generation: I forgot. nothing right now though. don't worry about it. correct_vs_incorrect_instances: will print the correctly classified instances vs the incorrectly classified instances. Note: Cataclysmic mutation is automatically implemented when needed. It is used to fill any empty spots in the new population.