<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[qq_35358021的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/qq_35358021</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; qq_35358021]]></copyright><item><title><![CDATA[构建词向量的数据读取]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/103049260</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/103049260</guid><author>qq_35358021</author><pubDate>Wed, 13 Nov 2019 15:29:10 +0800</pubDate><description><![CDATA[# 读取数据
def read_data(path_1, path_2, path_3):
    with open(path_1, 'r', encoding='utf-8') as f1, \
            open(path_2, 'r', encoding='utf-8') as f2, \
            open(path_3, 'r', encoding='utf...]]></description><category></category></item><item><title><![CDATA[词向量数据预处理参考]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/103048553</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/103048553</guid><author>qq_35358021</author><pubDate>Wed, 13 Nov 2019 14:51:54 +0800</pubDate><description><![CDATA[预处理
def parse_data(path):
    df = pd.read_csv(path, encoding='utf-8')
    data_x = df.Question.str.cat(df.Dialogue)
    data_y = []
    if 'Report' in df.columns:
        data_y = df.Report
    retur...]]></description><category></category></item><item><title><![CDATA[python_h2o实现梯度提升树算法]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/93600683</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/93600683</guid><author>qq_35358021</author><pubDate>Tue, 25 Jun 2019 10:57:05 +0800</pubDate><description><![CDATA[from h2o.estimators.gbm import H2OGradientBoostingEstimator

# 读取数据
data = h2o.import_file(path='data/allyears2k.csv')
# 分割数据
train,test = data.split_frame([.9])
# 构建x和y
myY = "IsDepDelayed"
myX = ["O...]]></description><category></category></item><item><title><![CDATA[python--h2o实现广义线性模型]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/93600154</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/93600154</guid><author>qq_35358021</author><pubDate>Tue, 25 Jun 2019 10:49:00 +0800</pubDate><description><![CDATA[%matplotlib inline
import random, os, sys
import h2o
import pandas
import pprint
import operator
import matplotlib
from h2o.estimators.glm import H2OGeneralizedLinearEstimator
from h2o.estimators.gbm ...]]></description><category></category></item><item><title><![CDATA[python-featuretools-advanced-featuretools]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92839310</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92839310</guid><author>qq_35358021</author><pubDate>Wed, 19 Jun 2019 17:33:33 +0800</pubDate><description><![CDATA[from sklearn.cluster import KMeans
import featuretools as ft
import featuretools.variable_types as vtypes
from featuretools.primitives import make_agg_primitive
from tsfresh.feature_extraction.feature...]]></description><category></category></item><item><title><![CDATA[python-featuretools-feature-selection]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92838728</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92838728</guid><author>qq_35358021</author><pubDate>Wed, 19 Jun 2019 17:16:02 +0800</pubDate><description><![CDATA[import featuretools as ft

# 定义EntitySet
es = ft.EntitySet(id = 'engines')
es = es.entity_from_dataframe(dataframe = train,
                              entity_id = 'obs',
                           ...]]></description><category></category></item><item><title><![CDATA[python-featuretools生成新特征]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92838005</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92838005</guid><author>qq_35358021</author><pubDate>Wed, 19 Jun 2019 16:55:45 +0800</pubDate><description><![CDATA[import featuretools as ft

# 定义EntitySet
es = ft.EntitySet(id = 'clients')
# 添加entity到EntitySet
es = es.entity_from_dataframe(entity_id = 'app', dataframe = app, index = 'SK_ID_CURR', variable_types=a...]]></description><category></category></item><item><title><![CDATA[python-autosklearn-LDA]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92834002</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92834002</guid><author>qq_35358021</author><pubDate>Wed, 19 Jun 2019 15:45:52 +0800</pubDate><description><![CDATA[from ConfigSpace.configuration_space import ConfigurationSpace
from ConfigSpace.hyperparameters import UniformFloatHyperparameter, \
    UniformIntegerHyperparameter, CategoricalHyperparameter

import...]]></description><category></category></item><item><title><![CDATA[python-autosklearn-RidgeRegression]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92833712</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92833712</guid><author>qq_35358021</author><pubDate>Wed, 19 Jun 2019 15:41:45 +0800</pubDate><description><![CDATA[from ConfigSpace.configuration_space import ConfigurationSpace
from ConfigSpace.hyperparameters import UniformFloatHyperparameter, \
    UniformIntegerHyperparameter, CategoricalHyperparameter

import...]]></description><category></category></item><item><title><![CDATA[python-autosklearn-MLPClassifier]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92833241</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92833241</guid><author>qq_35358021</author><pubDate>Wed, 19 Jun 2019 15:36:20 +0800</pubDate><description><![CDATA[from ConfigSpace.configuration_space import ConfigurationSpace
from ConfigSpace.hyperparameters import CategoricalHyperparameter, \
    UniformIntegerHyperparameter, UniformFloatHyperparameter

import...]]></description><category></category></item><item><title><![CDATA[python-smac-svm实例]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92798892</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92798892</guid><author>qq_35358021</author><pubDate>Wed, 19 Jun 2019 08:35:57 +0800</pubDate><description><![CDATA[import logging
import numpy as np
from sklearn import svm, datasets
from sklearn.model_selection import cross_val_score

# Import ConfigSpace and different types of parameters
from smac.configspace im...]]></description><category></category></item><item><title><![CDATA[python-smac-自动化优化函数实例]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92796096</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92796096</guid><author>qq_35358021</author><pubDate>Tue, 18 Jun 2019 19:38:38 +0800</pubDate><description><![CDATA[import logging

from smac.facade.func_facade import fmin_smac


def rosenbrock_2d(x):
    """ The 2 dimensional Rosenbrock function as a toy model
    The Rosenbrock function is well know in the optim...]]></description><category></category></item><item><title><![CDATA[python-smac-randomforest自动化调参]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92796019</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92796019</guid><author>qq_35358021</author><pubDate>Tue, 18 Jun 2019 16:55:02 +0800</pubDate><description><![CDATA[import logging
import os
import inspect
import numpy as np
from sklearn.metrics import make_scorer
from sklearn.model_selection import cross_val_score
from sklearn.ensemble import RandomForestRegresso...]]></description><category></category></item><item><title><![CDATA[python-autosklearn-randomsearch]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92794361</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92794361</guid><author>qq_35358021</author><pubDate>Tue, 18 Jun 2019 15:52:28 +0800</pubDate><description><![CDATA[import sklearn.model_selection
import sklearn.datasets
import sklearn.metrics

from smac.facade.roar_facade import ROAR
from smac.scenario.scenario import Scenario

import autosklearn.classification

...]]></description><category></category></item><item><title><![CDATA[python-autosklearn-metric]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92790655</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92790655</guid><author>qq_35358021</author><pubDate>Tue, 18 Jun 2019 15:08:17 +0800</pubDate><description><![CDATA[import numpy as np
import sklearn.model_selection
import sklearn.datasets
import sklearn.metrics
import autosklearn.classification
import autosklearn.metrics


def accuracy(solution, prediction):
    ...]]></description><category></category></item><item><title><![CDATA[python-autosklearn-openml-处理连续分类数据]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92789345</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92789345</guid><author>qq_35358021</author><pubDate>Tue, 18 Jun 2019 14:52:25 +0800</pubDate><description><![CDATA[import sklearn.model_selection
import sklearn.datasets
import sklearn.metrics
import autosklearn.classification
import openml


def main():
    openml.config.apikey = '610344db6388d9ba34f6db45a3cf71de...]]></description><category></category></item><item><title><![CDATA[python-autosklearn-regression]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92771369</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92771369</guid><author>qq_35358021</author><pubDate>Tue, 18 Jun 2019 11:18:58 +0800</pubDate><description><![CDATA[import sklearn.model_selection
import sklearn.datasets
import sklearn.metrics
import autosklearn.regression

def main():
    X, y = sklearn.datasets.load_boston(return_X_y=True)
    feature_types = ([...]]></description><category></category></item><item><title><![CDATA[python-autosklearn-sequence-usage]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92769908</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92769908</guid><author>qq_35358021</author><pubDate>Tue, 18 Jun 2019 11:04:34 +0800</pubDate><description><![CDATA[import sklearn.model_selection
import sklearn.datasets
import sklearn.metrics
import autosklearn.classification


def main():
    X, y = sklearn.datasets.load_breast_cancer(return_X_y=True)
    X_trai...]]></description><category></category></item><item><title><![CDATA[python-autosklearn-多进程]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92769027</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92769027</guid><author>qq_35358021</author><pubDate>Tue, 18 Jun 2019 10:55:17 +0800</pubDate><description><![CDATA[import multiprocessing
import shutil
import sklearn.model_selection
import sklearn.datasets
import sklearn.metrics
from autosklearn.metrics import accuracy
from autosklearn.classification import AutoS...]]></description><category></category></item><item><title><![CDATA[python-autosklearn-单个机器上的并行]]></title><link>https://blog.youkuaiyun.com/qq_35358021/article/details/92765054</link><guid>https://blog.youkuaiyun.com/qq_35358021/article/details/92765054</guid><author>qq_35358021</author><pubDate>Tue, 18 Jun 2019 10:12:33 +0800</pubDate><description><![CDATA[import sklearn.model_selection
import sklearn.datasets
import sklearn.metrics
import autosklearn.classification


def main():
    X, y = sklearn.datasets.load_breast_cancer(return_X_y=True)
    X_trai...]]></description><category></category></item></channel></rss>