本文整理汇总了Python中classifier.Classifier.ensemble_preds方法的典型用法代码示例。如果您正苦于以下问题：Python Classifier.ensemble_preds方法的具体用法？Python Classifier.ensemble_preds怎么用？Python Classifier.ensemble_preds使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类classifier.Classifier的用法示例。
在下文中一共展示了Classifier.ensemble_preds方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: len
# 需要导入模块: from classifier import Classifier [as 别名]
# 或者: from classifier.Classifier import ensemble_preds [as 别名]
from image import Image
from preprocess import Preprocess
from classifier import Classifier
from log_loss import log_loss
from postprocess import PostProcess
genders = Image.genders()
d, _ = Image.data()
matrix = Preprocess.to_matrix(d)
print matrix.shape
matrix = Preprocess.remove_constants(matrix)
print matrix.shape
matrix = Preprocess.scale(matrix)
matrix = Preprocess.polynomial(matrix, 2)
matrix = Preprocess.scale(matrix)
print matrix.shape
matrix = matrix.tolist()
half = len(matrix)/2
train, cv = matrix[:half], matrix[half:]
train_genders, cv_genders = genders[:half], genders[half:]
cv_genders = cv_genders[0::4]
preds = Classifier.ensemble_preds(train, train_genders, cv)
print "Score: ", log_loss(preds, cv_genders)
示例2: len
# 需要导入模块: from classifier import Classifier [as 别名]
# 或者: from classifier.Classifier import ensemble_preds [as 别名]
from image import Image
from preprocess import Preprocess
from classifier import Classifier
from postprocess import PostProcess
genders = Image.genders()
all_data, ids = Image.all()
matrix = Preprocess.to_matrix(all_data)
matrix = Preprocess.remove_constants(matrix)
matrix = Preprocess.scale(matrix)
matrix = Preprocess.polynomial(matrix, 2)
matrix = Preprocess.scale(matrix)
matrix = matrix.tolist()
train = matrix[:1128]
test = matrix[1128:]
test_ids = ids[1128:]
print len(train)
print len(test)
print len(test_ids)
print len(ids)
print len(matrix)
preds = Classifier.ensemble_preds(train, genders, test) # real
# preds = Classifier.ensemble_preds(train, genders, train) # fake
# for creating submission file
PostProcess.submission(test_ids, preds)