机器学习-机器学习库Scikit-learn 黄海广 副教授 2 本章目录 01 Scikit-learn概述 02 Scikit-learn主要用法 03 Scikit-learn案例 3 1.Scikit-learn概述 01 Scikit-learn概述 02 Scikit-learn主要用法 03 Scikit-learn案例 4 1.Scikit-learn概述 Scikit-learn概述 Scikit-learn是基于NumPy、 SciPy和 Matplotlib的开源Python机器学习 包,它封装了一系列数据预处理、机器学习算法、模型选择等工具,是数 据分析师首选的机器学习工具包。 自2007年发布以来，scikit-learn已经成为Python重要的机器学习库了， scikit-learn简称sklearn，支持包括分类，回归，降维和聚类四大机器学 习 习算法。还包括了特征提取，数据处理和模型评估三大模块。 5 6 2.Scikit-learn主要用法 01 Scikit-learn概述 02 Scikit-learn主要用法 03 Scikit-learn案例 7 X_train | 训练数据. X_test | 测试数据. X | 完整数据. 符号标记 2.Scikit-learn主要用法 y_train | 训练集标签.

Search for a specific package named ‘scikit-learn’: conda search scikit-learn Search for packages containing ‘scikit’ in the package name: conda search scikit Note that your shell may expand ‘*’ before is sometimes necessary to use single or double quotes around the query. conda search ‘scikit’ conda search “*scikit” Search for packages for 64-bit Linux (by default, packages for your current platform satisfy dependencies. For example, executing: conda install conda-forge::scikit-learn will confine all future changes to the scikit-learn package in the environment to the conda-forge channel, until the

Search for a specific package named ‘scikit-learn’: conda search scikit-learn Search for packages containing ‘scikit’ in the package name: conda search scikit Note that your shell may expand ‘*’ before is sometimes necessary to use single or double quotes around the query. conda search ‘scikit’ conda search “*scikit” Search for packages for 64-bit Linux (by default, packages for your current platform satisfy dependencies. For example, executing: conda install conda-forge::scikit-learn will confine all future changes to the scikit-learn package in the environment to the conda-forge channel, until the

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 18 可视化 Visualization 234 19 Scikit-learn API 235 20 工具 236 20.1 CustomObjectScope [source] . . . . . . . . . . . . . . . . . . . SGD(lr=0.01, momentum=0.9, nesterov=True)) 现在，你可以批量地在训练数据上进行迭代了： # x_train 和 y_train 是 Numpy 数组 -- 就像在 Scikit-Learn API 中一样。 model.fit(x_train, y_train, epochs=5, batch_size=32) 或者，你可以手动地将批次的数据提供给模型： model create(prog='dot', format='svg')) SCIKIT-LEARN API 235 19 Scikit-learn API Scikit-Learn API 的封装器 你可以使用 Keras 的顺序模型 (仅限单一输入) 作为 Scikit-Learn 工作流程的一部分，通过在 此找到的包装器: keras.wrappers.scikit_learn.py. 有两个封装器可用: keras

tions. Building NumPy with BLAS variants If you build NumPy with MKL, you also need to build SciPy, scikit-learn, and anything else using BLAS also with MKL. It is important to ensure that these “variants” Search for a specific package named 'scikit-learn': conda search scikit-learn Search for packages containing 'scikit' in the package name: conda search *scikit* Note that your shell may expand '*' sometimes necessary to use single or double quotes around the query: conda search '*scikit' conda search "*scikit*" Search for packages for 64-bit Linux (by default, packages for your current platform

3: Python libraries Keras depends on the following python libraries.  Numpy  Pandas  Scikit-learn  Matplotlib  Scipy  Seaborn Hopefully, you have installed all the above libraries macosx_10_10_intel.macosx_10_10_x86_64.whl (14.4MB) |████████████████████████████████| 14.4MB 2.8MB/s scikit-learn It is an open source machine learning library. It is used for classification, regression Keras 6  joblib 0.11 or higher. Now, we install scikit-learn using the below command: pip install -U scikit-learn Seaborn Seaborn is an amazing library that allows you to easily

cosine/fasttext cosine • wmd：计算wmd特征 • esim：计算lstm-esim特征 • tensorflow：计算transformer-esim特征 • scikit learn：调用LR训练模型 各个击破－评估 • 评估数据 Ø 领域均衡：6个领域，每个领域50个知识点 Ø 评估数据对标训练数据：每个知识点12个相似问用于训练，3个相似问用于评估 • 降低资源占用 Ø 方便灵活扩容 Ø 资源充分利用 • 服务框架 Ø http：短链接，简单，开发方便 Ø grpc：长链接，安全性 3 Python开发的利与弊 优势总结、缺点举例 机器学习库scikit learn 计算库numpy 文本挖掘库gensim 深度学习库tensorflow等 强大的第三方 工具库 支持其它语言 优势互补 开发便捷 调试简单 语法简单 易用性强

tions. Building NumPy with BLAS variants If you build NumPy with MKL, you also need to build SciPy, scikit-learn, and anything else using BLAS also with MKL. It is important to ensure that these “variants” Search for a specific package named 'scikit-learn': conda search scikit-learn Search for packages containing 'scikit' in the package name: conda search *scikit* Note that your shell may expand '*' sometimes necessary to use single or double quotes around the query: conda search '*scikit' conda search "*scikit*" Search for packages for 64-bit Linux (by default, packages for your current platform

tions. Building NumPy with BLAS variants If you build NumPy with MKL, you also need to build SciPy, scikit-learn, and anything else using BLAS also with MKL. It is important to ensure that these “variants” Search for a specific package named 'scikit-learn': conda search scikit-learn Search for packages containing 'scikit' in the package name: conda search *scikit* Note that your shell may expand '*' sometimes necessary to use single or double quotes around the query: conda search '*scikit' conda search "*scikit*" Search for packages for 64-bit Linux (by default, packages for your current platform

tions. Building NumPy with BLAS variants If you build NumPy with MKL, you also need to build SciPy, scikit-learn, and anything else using BLAS also with MKL. It is important to ensure that these “variants” Search for a specific package named 'scikit-learn': conda search scikit-learn Search for packages containing 'scikit' in the package name: conda search *scikit* Note that your shell may expand '*' sometimes necessary to use single or double quotes around the query: conda search '*scikit' conda search "*scikit*" Search for packages for 64-bit Linux (by default, packages for your current platform