本文整理匯總了Python中weka.filters.Filter.to_source方法的典型用法代碼示例。如果您正苦於以下問題：Python Filter.to_source方法的具體用法？Python Filter.to_source怎麽用？Python Filter.to_source使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類weka.filters.Filter的用法示例。
在下文中一共展示了Filter.to_source方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: main
# 需要導入模塊: from weka.filters import Filter [as 別名]
# 或者: from weka.filters.Filter import to_source [as 別名]
def main():
"""
Just runs some example code.
"""
# load a dataset
iris = helper.get_data_dir() + os.sep + "iris.arff"
helper.print_info("Loading dataset: " + iris)
loader = Loader("weka.core.converters.ArffLoader")
data = loader.load_file(iris)
# remove class attribute
helper.print_info("Removing class attribute")
remove = Filter(classname="weka.filters.unsupervised.attribute.Remove", options=["-R", "last"])
remove.inputformat(data)
filtered = remove.filter(data)
# use MultiFilter
helper.print_info("Use MultiFilter")
remove = Filter(classname="weka.filters.unsupervised.attribute.Remove", options=["-R", "first"])
std = Filter(classname="weka.filters.unsupervised.attribute.Standardize")
multi = MultiFilter()
multi.filters = [remove, std]
multi.inputformat(data)
filtered_multi = multi.filter(data)
# output datasets
helper.print_title("Input")
print(data)
helper.print_title("Output")
print(filtered)
helper.print_title("Output (MultiFilter)")
print(filtered_multi)
# load text dataset
text = helper.get_data_dir() + os.sep + "reutersTop10Randomized_1perc_shortened.arff"
helper.print_info("Loading dataset: " + text)
loader = Loader("weka.core.converters.ArffLoader")
data = loader.load_file(text)
data.class_is_last()
# apply StringToWordVector
stemmer = Stemmer(classname="weka.core.stemmers.IteratedLovinsStemmer")
stopwords = Stopwords(classname="weka.core.stopwords.Rainbow")
tokenizer = Tokenizer(classname="weka.core.tokenizers.WordTokenizer")
s2wv = StringToWordVector(options=["-W", "10", "-L", "-C"])
s2wv.stemmer = stemmer
s2wv.stopwords = stopwords
s2wv.tokenizer = tokenizer
s2wv.inputformat(data)
filtered = s2wv.filter(data)
helper.print_title("Input (StringToWordVector)")
print(data)
helper.print_title("Output (StringToWordVector)")
print(filtered)
# partial classname
helper.print_title("Creating filter from partial classname")
clsname = ".Standardize"
f = Filter(classname=clsname)
print(clsname + " --> " + f.classname)
# source code
helper.print_info("Generate source code")
bolts = helper.get_data_dir() + os.sep + "labor.arff"
helper.print_info("Loading dataset: " + bolts)
loader = Loader("weka.core.converters.ArffLoader")
data = loader.load_file(bolts)
replace = Filter(classname="weka.filters.unsupervised.attribute.ReplaceMissingValues")
replace.inputformat(data)
replace.filter(data)
print(replace.to_source("MyReplaceMissingValues", data))