public override ILearnAlgorithmConf getConf(int CountFeatures) { ILearnAlgorithmConf result = new ESConfig(); result.Init(CountFeatures); return(result); }
/// <summary> /// 获取客户端 /// </summary> /// <param name="esConfig"></param> /// <returns></returns> public ElasticClient GetClient(ESConfig esConfig) { var uris = esConfig.Urls.Split(',').ToList().Select(i => Uri.TryCreate(i, UriKind.Absolute, out Uri u) ? u : null); //配置节点地址,以,分开 var settings = new ConnectionSettings(new StaticConnectionPool(uris)) .BasicAuthentication(esConfig.User, esConfig.Pwd) //用户名和密码 .RequestTimeout(TimeSpan.FromSeconds(30)); //请求配置参数 this.Client = new ElasticClient(settings); //linq请求客户端初始化 return(this.Client); }
protected override void fill_conf() { ESConfig conf1 = conf as ESConfig; conf1.ESCInitType = type_init; conf1.ESCMutateAlg = type_mutate; conf1.ESCCrossoverType = type_cross; conf1.ESCCrossoverPropability = pcross; conf1.ESCCountCrossoverPoint = (int)cpcross; conf1.ESCAngleRotateB = angleR; conf1.ESCCountIteration = (int)iterate; conf1.ESCPopulationSize = (int)cindiv; conf1.ESCCountChild = (int)cchild; }
public virtual void Init(ILearnAlgorithmConf Conf) { Config = Conf as ESConfig; count_populate = Config.ESCPopulationSize; count_child = Config.ESCCountChild; count_iterate = Config.ESCCountIteration; coef_t1 = Config.ESCT1; coef_t2 = Config.ESCT2; param_crossover = Config.ESCCrossoverPropability; alg_cross = Config.ESCCrossoverType; type_init = Config.ESCInitType; count_Multipoint = Config.ESCCountCrossoverPoint; type_mutate = Config.ESCMutateAlg; b_ro = Config.ESCAngleRotateB; main_pop = new Population(count_populate, count_child, result.CountFeatures, result.LearnSamplesSet); main_pop.init_first(result.RulesDatabaseSet[0], rand, type_init); }
public override int Run(string[] args) { Console.WriteLine("Start"); fill_params(args); Console.WriteLine("Params get \nfile in {0} ", file_in); Approx_learn_set = BaseUFSLoader.LoadLearnFromUFS(file_in); Console.WriteLine("Tra load"); Approx_test_set = BaseUFSLoader.LoadTestFromUFS(file_in); Console.WriteLine("Tst load"); conf = new ESConfig(); conf.Init(Approx_learn_set.CountVars); fill_conf(); Console.WriteLine("Conf Filed"); Approx_Singletone = new SAFuzzySystem(Approx_learn_set, Approx_test_set); Approx_Singletone = SAFSUFSLoader.loadUFS(Approx_Singletone, file_in); Console.WriteLine("Classifier created"); optimaze = new ESMethod(); Approx_Singletone = optimaze.TuneUpFuzzySystem(Approx_Singletone, conf); Console.WriteLine("Optimization complite"); SAFSUFSWriter.saveToUFS(Approx_Singletone, file_out); Console.WriteLine("Saved"); return(1); }
/// <summary> /// /// </summary> /// <param name="esConfig"></param> public ESService(ESConfig esConfig) => GetClient(esConfig);
private List <ILearnAlgorithmConf> initAlgoritmsConfigs(int CountFeature) { List <ILearnAlgorithmConf> result = new List <ILearnAlgorithmConf>(); if (isTermShrink) { result.Add(new OptimizeTermShrinkAndRotateConf()); } if (isRuleShrink) { result.Add(new OptimizeRullesShrinkConf()); } if (isUnionTerm) { result.Add(new UnionTermsConf()); } if (isLindBreakCross) { result.Add(null); } if (isPSO) { for (int i = 0; i < countPSO; i++) { result.Add(new PSOSearchConf()); } } if (isANT) { for (int i = 0; i < countANT; i++) { result.Add(new MACOSearchConf()); } } if (isBEE) { for (int i = 0; i < countBEE; i++) { result.Add(new BeeStructureConf()); } } if (isES) { for (int i = 0; i < countES; i++) { ESConfig method = new ESConfig(); method.Init(CountFeature); result.Add(method); } } if (isGA) { for (int i = 0; i < countGA; i++) { GeneticConf method = new GeneticConf(); method.Init(CountFeature); result.Add(method); } } /* if (isBFO) * { * for (int i = 0; i < countBFO; i++) * { * BacterialForagingOptimization.Base.BacteryAlgorithmConfig method = new BacterialForagingOptimization.Base.BacteryAlgorithmConfig(); * method.Init(CountFeature); * result.Add(method); * } * } */ return(result); }