Updated Aug 4, 2024 Python yunusbagriacik / sales-analysis-and-linear-predictive-model Star 0 Code Issues Pull requests In this repository, sales analysis of 5-year-period is analysed. Lots of linear regression model have been applied. Finally, ensemble method is applied. data-science mach...
Regression is performed on continuous data, while classification is performed on discrete data. Regression can be anything from predicting someone's age, the house of a price, or value of any variable. Classification includes predicting whatclasssomething belongs to (such as whether a tumor is beni...
MachineLearning_Python/LinearRegression/LinearRegression.py/ Jump to cclaussModernize Python 2 code to get ready for Python 3 Latest commit202ff3bon Jan 4, 2018History 1contributor 116 lines (86 sloc)3.76 KB RawBlame #-*- coding: utf-8 -*- ...
J_history=np.zeros((num_iters,1))foriterinrange(num_iters):# 对J求导,得到 alpha/m*(WX-Y)*x(i),(3,m)*(m,1)X(m,3)*(3,1)=(m,1)theta=theta-(alpha/m)*(X.T.dot(X.dot(theta)-y))J_history[iter]=computeCost(X,y,theta)returnJ_history,theta iterations=10000#迭代次数 alph...
机器学习(三)---多变量线性回归(Linear Regression with Multiple Variables) 同样是预测房价问题 如果有多个特征值 那么这种情况下 假设h表示为 公式可以简化为 两个矩阵相乘 其实就是所有参数和变量相乘再相加 所以矩阵的乘法才会是那样 那么他的代价函数就是 同样是寻找...
The script shown in the steps below is main.py — which resides in the GitHub repository and is forked from the “Dive Into Deep learning” example repository. You can find code samples within the pytorch directory. For our regression example, you’ll need the following: Python 3 PyTorch ...
Tensorflow是目前非常流行的deeplearning框架,学习Tensorflow最好的方法是github上的tf项目https://github.com/tensorflow/tensorflow 或者阅读极客学院主导翻译的中文教程http://wiki.jikexueyuan.com/project/tensorflow-zh/how_tos/reading_data.html。 此处对tensorflow的基本语法不予赘述,直接贴上源码: ...
[57] is a well known Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised ML problems. It supports tools for classification, regression, clustering, dimensionality reduction, model selection and preprocessing. It is based ...
Basic mathematical knowledge or foundation is recommended; prior programming experience in Python will be beneficial. The hands-on examples and coding exercises make it suitable for anyone eager to apply regression concepts in real-world scenarios. What you will learn Understand the fundamentals of ...
In Python, we can find the same data set in the scikit-learn module. import numpy as np import pandas as pd from numpy.linalg import inv from sklearn.datasets import load_boston from statsmodels.regression.linear_model import OLS Next, we can load the Boston data using the load_boston ...