Exemplos de cons_train_sample_for_svm em Python

Exemplo n.º 1

def process(parse_result):
    """
    desc: This function use to construct the standard format file and save some parameters
    params: the instance returned by function--parser()
    return: None
    date: 2013-10-30
    """
    input_file = parse_result.input_file.strip()
    if os.path.isfile(input_file):
        dic_key = parse_result.dic_key.strip()
        dest_file = parse_result.dest_file
        tms.cons_train_sample_for_svm(input_file, dic_key, sample_save_path=dest_file, str_splitTag="^")
        print "第三步<libsvm格式构造>处理结果：\n"
        print "构造好的libsvm格式文件为：%s\n\n\n" % dest_file
    else:
        print "输入文件不存在！\n"

Exemplo n.º 2

def process(parse_result):
    '''
    desc: This function use to construct the standard format file and save some parameters
    params: the instance returned by function--parser()
    return: None
    date: 2013-10-30
    '''
    input_file = parse_result.input_file.strip()
    if os.path.isfile(input_file):
        dic_key = parse_result.dic_key.strip()
        dest_file = parse_result.dest_file
        tms.cons_train_sample_for_svm(input_file,
                                      dic_key,
                                      sample_save_path=dest_file,
                                      str_splitTag="^")
        print "第三步<libsvm格式构造>处理结果：\n"
        print "构造好的libsvm格式文件为：%s\n\n\n" % dest_file
    else:
        print "输入文件不存在！\n"

Exemplo n.º 3

Arquivo: test.py Projeto: winater/SimpleEarlyWarningSystem

#tms.tms_analysis("../result/linear_title.result",step=4,output_file="../data/linear_title.analysis",indexes=[0,1,2],predicted_label_index=0,predicted_value_index=1,true_label_index=2,min=0,max=2)=======
#import tms
#tms.tms_predict_multi("../data/weijin.test", ["../data/aliws/model/lineartitle.config","../data/aliws/model/lineartitle_content.config","../data/aliws/model/svmtitle.config","../data/aliws/model/svmtitle_content.config"],[[2],[2,3],[2],[2,3]],result_indexes=[0,1,2,3,4],result_save_path="../data/weijin.result")>>>>>>> .r167

#先根据训练样本取得词典后，然后再根据词典把测试样本转换为相应的格式。
filepath = u"E:\\算法与技术学习\\y语料库\\PaperCopus\\"
trainFile = u"reuters_raw_train_0.txt"
testFile = u"reuters_raw_test_0.txt"
tms.tms_train(
    os.path.join(filepath, trainFile),
    main_save_path=filepath,
    stopword_filename=u"E:\\算法与技术学习\\y语料库\\PaperCopus\\stopwords.txt",
    svm_type="liblinear",
    config_name="weijin_ik_20120110.config",
    dic_name="weijin_ik_20120110.key",
    model_name="weijin_ik_20120110.model",
    train_name="weijin_ik_20120110.train",
    param_name="weijin_ik_20120110.param",
    ratio=0.4,
    seg=0,
    local_fun="tf",
    global_fun="rf",
    str_splitTag=" ",
    tc_splitTag="\t")
tms.cons_train_sample_for_svm(
    os.path.join(filepath, testFile),
    u"E:\\算法与技术学习\\y语料库\\PaperCopus\\model\\weijin_ik_20120110.key",
    u"E:\\算法与技术学习\\y语料库\\PaperCopus\\new.txt",
    local_fun="tf",
    str_splitTag=" ",
    tc_splitTag="\t")

Exemplo n.º 4

Arquivo: test.py Projeto: Kevin-yj-Zhao/JunkFilter-for-MeiPai

#!/usr/bin/python
#_*_ coding: utf-8 _*_
#author: 张知临 [email protected]
import tms,os
#tms.tms_train("../data/weijin.train",indexes=[4],main_save_path="../model/",stopword_filename="../data/stopwords.txt",svm_type="liblinear",config_name="linear_title.config",dic_name="linear_title.key",model_name="linear_title.model",train_name="linear_title.train",param_name="linear_title.param",ratio=0.4,seg=1,local_fun="tf",global_fun="rf")
#tms.tms_predict_multi("../data/weijin.test",config_files=["../model/model/linear_title.config"],indexes_lists=[[4]],result_save_path="../result/linear_title.result",result_indexes=[0],seg=1)
#tms.tms_analysis("../result/linear_title.result",step=4,output_file="../data/linear_title.analysis",indexes=[0,1,2],predicted_label_index=0,predicted_value_index=1,true_label_index=2,min=0,max=2)=======
#import tms
#tms.tms_predict_multi("../data/weijin.test", ["../data/aliws/model/lineartitle.config","../data/aliws/model/lineartitle_content.config","../data/aliws/model/svmtitle.config","../data/aliws/model/svmtitle_content.config"],[[2],[2,3],[2],[2,3]],result_indexes=[0,1,2,3,4],result_save_path="../data/weijin.result")>>>>>>> .r167


#先根据训练样本取得词典后，然后再根据词典把测试样本转换为相应的格式。
filepath = u"E:\\算法与技术学习\\y语料库\\PaperCopus\\"
trainFile=u"reuters_raw_train_0.txt"
testFile=u"reuters_raw_test_0.txt"
tms.tms_train(os.path.join(filepath,trainFile),main_save_path=filepath,stopword_filename=u"E:\\算法与技术学习\\y语料库\\PaperCopus\\stopwords.txt",svm_type="liblinear",config_name="weijin_ik_20120110.config",dic_name="weijin_ik_20120110.key",model_name="weijin_ik_20120110.model",train_name="weijin_ik_20120110.train",param_name="weijin_ik_20120110.param",ratio=0.4,seg=0,local_fun="tf",global_fun="rf",str_splitTag=" ",tc_splitTag="\t")
tms.cons_train_sample_for_svm(os.path.join(filepath,testFile), u"E:\\算法与技术学习\\y语料库\\PaperCopus\\model\\weijin_ik_20120110.key",u"E:\\算法与技术学习\\y语料库\\PaperCopus\\new.txt", local_fun="tf",str_splitTag=" ",tc_splitTag="\t")