线性回归(Linear regression)是利用回归方程(函数)对一个或多个自变量(特征值)和因变量(目标值)之间关系进行建模的一种分析方式。 通用公式: 应用场景: 1.房价预测 2.销售额度预测 3.贷款额度预测 一.案例背景介绍 # -*- coding: utf-8 -*- # @Time : 2019/11/12 11:46 # @Author : from sklearn....
MultipleLines,InternetService,OnlineSecurity,OnlineBackup,DeviceProtection,TechSupport,StreamingTV,StreamingMovies, andContracthave 3 unique values each. The most common value for most of these variables is 'No', except forInternetService(most common is 'Fiber optic') andContract(most common is 'Month...
The data used in this report is downloaded fromKaggle’sHeart Failure Prediction Dataset(Heart Failure Prediction Dataset | Kaggle). This dataset has created by combining different datasets already available independently but not combined before. In this dataset, 5 heart datasets are combined over 11 ...
Bagging classifier uses a process called bootstrapped dataset to create multiple datasets from one original dataset and runs algorithm on each one of them. Here is an image to show how bootstrapped dataset works. Resampling from original dataset to bootstrapped datasets Source: https://uc-r.github...
You will build visualizations, correlate multiple time series, and evaluate the relationships between the components. You can use Kaggle’s dataset to predict air pollution measurements using time series analysis and datasets for weather information. Predict Personality Types on Myers-Briggs Personality ...
from sklearn.datasets import make_blobs from sklearn.model_selection import train_test_split # 构建数据集 X, y = make_blobs(n_samples=100000) # 数据集划分 val_ratio = 0.2 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=val_ratio) ...
Step 1. Imports and Datasets Step 2. Regression 2-1. Linear Regression 2-2. Decision Tree Regressor 2-3. Random Forest Regressor Step 3. Classification 3-1. Preparing Data 3-2. One-Hot Encoding 3-3. Logistic Regression 3-4. KNN 3-5. SVM 3-6. GaussianNB 3-7. Decision Tree 3-8....
("tokenize datasets ... iter: over weak") tokenized_texts_train, tokenized_texts_test, tokenized_texts_test2 = tokenize_datasets (vs_counters, train, lm_data, test) print("verctorize datasets ...iter: over weak") tf_train, tf_test = vectorizer_of_data(tokenized_texts_train,tokenized_...
SurveyDf<-fread("../Datasets/kagglesurvey2017/multipleChoiceResponses.csv") #for faster data reading## Read 59.5% of 16817 rows Read 16716 rows and 228 (of 228) columns from 0.023 GB file in 00:00:03Copy Most preferred blog sites for learning data science. ...
tsf-not-mnist Learn simple data curation by creating a pickle with formatted datasets for training, development and testing in TensorFlow. tsf-fully-connected Progressively train deeper and more accurate models using logistic regression and neural networks in TensorFlow. tsf-regularization Explore regulariz...