接下来,上传最近写的SGD Python代码,首先是引入模块:logisticRegression.py,这里面定义了两个class:LogisticRegressionWithSGD,LRModel,还有全局函数RMSE,loadDataSet和sigmoid函数。后面是测试代码,主要是参数调优。 logisticRegression.py: View Code 测试代码,把最优模型
You will build a logistic regression classifier to recognize cats. This assignment will step you through how to do this with a Neural Network mindset, and so will also hone your intuitions about deep learning. Instructions: Do not use loops (for/while) in your code, unless the instructions ...
其中os模块主要用于在本地查找dataset文件,具有目录的处理以及文件的判断等函数;gzip模块提供了一些简单的对文件进行压缩和解压缩的函数功能;cPickle模块可以对任意一种类型的python对象进行序列化操作。 1、程序中的os模块 在load_data(dataset)函数中,使用到的主要是os.path模块,使用到的函数是: os.path.split(path...
# Logistic Regression with a Neural Network mindset# Initializing parameters# Calculating the cost function and its gradient# Using an optimization algorithm (gradient descent)""" numpy is the fundamental package for scientific computing with Python. h5py is a common package to interact with a datas...
Logostic Regression (LR) 是典型的二分类算法,而不是回归算法。一般来讲,机器学习实用为先,对于新数据集可以先用 LR 做个试验,能用简单的算法不必刻意追求复杂高级。 Sigmoid 函数:自变量取值范围:R; 值域:[0,1] f(x)=1/(1+e−x) 可以将任意输入映射到[0,1]区间。在线性回归中得到预测值,再将该值...
机器学习二 逻辑回归作业、逻辑回归(Logistic Regression) 57维特征,2分类问题。采用逻辑回归方法。但是上述数据集在kaggle中没法下载,于是只能用替代的方法了,下了breast-cancer-wisconsin数据集。 链接在这http://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/breast-cancer-wisconsin....
Python代码示例 import csv import numpy as np import matplotlib.pyplot as plt def loadCSV(filename): ''' function to load dataset ''' with open(filename,"r") as csvfile: lines = csv.reader(csvfile) dataset = list(lines) for i in range(len(dataset)): dataset[i] = [float(x) for...
df_german=pd.read_excel("D:/study/5/code/python/python Data analysis and mining/class/dataset/german.xls") y=df_german.ix[:,-1] x=df_german.ix[:,:-1] l1 = [] for i in range(1000): print('***'*50) print('第',i+1,'次test') #...
microsoftml.rx_logistic_regression(formula: str, data: [revoscalepy.datasource.RxDataSource.RxDataSource, pandas.core.frame.DataFrame], method: ['binary', 'multiClass'] = 'binary', l2_weight: float = 1, l1_weight: float = 1, opt_tol: float = 1e-07, memory_size: int = 20, init_...
How to Build & Evaluate a text classifier using Logistic Regression & Python's sklearn for NEWS categorization. Comes with Jupyter Notebook & Dataset.