sklearn datasets wine. model_selection import train_test_split from sklearn. Logistic Regression using Python Video The first part of this tutorial post goes over a toy dataset (digits dataset…. csdn已为您找到关于sklearn wine数据集 导入相关内容,包含sklearn wine数据集 导入相关文档代码介绍、相关教程视频课程,以及相关sklearn wine数据集 导入问答内容。为您解决当下相关问题,如果想了解更详细sklearn wine …. datasets import make_classification. In this we will using both for different dataset. Both the datasets contain numeric features of the relevant wine type. 小伙伴们大家好~o ( ̄  ̄)ブ,首先声明一下,我的开发环境 …. The white wine dataset has 4898 …. Once the libraries had been imported, I imported load_wine from sklearn. Decision tree analysis can help solve both classification & regression problems. import pandas as pd from sklearn import datasets from sklearn. pyplot as plt import pandas as pd 2- Load the Dataset dataset = pd. Splitting Datasets With the Sklearn train_test. Iris DataSet은 1930년대부터 시작된 고전적인 데이터셋이기 때문에 DataSet을 가져오는 방법에도 여러가지 방법이 존재합니다. Classes 3 수업 당 샘플 [59,71,48] 총 샘플 178 . In the below example the wine dataset is balanced by multiclass oversampling: import smote_variants as sv import sklearn. In the Wine Dataset available as open data in the UCI Machine Learning Repository, there are 177 wines with 13 attributes as mentioned: alcohol, malic acid, ash, alkalinity of ash, magnesium, total phenols, flavonoids, non-flavanoids phenols, proanthocyanins, color intensity, hue, OD280/OD325 diluted wines…. install sklearn in jupyter notebook. An introduction to machine learning with scikit-learn, python >>> from sklearn import datasets >>> iris = datasets. Fresh approach to Machine Learning in PHP. 4 ways to implement feature selection in Python for machine learning. datasets as datasets dataset= datasets. In this post, we’ll use the grid search capability from the sklearn library to find the best parameters for SVM. 하지만 가장 간단한 방법은 Scikit-Learn에 들어있는 Iris DataSet을 코드상으로 불러오는 …. Use the example dataset from the scikit-learn example. 먼저, sklearn에서 데이터셋을 가지고 있는 함수를 불러와야 한다 : from sklearn. We will walk through an example that involves training a model to tell what kind of wine will be “good” or “bad” based on a training set of wine chemical characteristics. load_wine (*, return_X_y= False , as_frame= False) [源码] 加载并返回葡萄酒数据集(分类)。 版本0. It is a classic and multi-class . # Print the data and check for yourself. In this article, we will look at different methods to select features from the dataset…. name: beer mac n cheese soup id: 499490 minutes: 45 contributor_id: 560491 submitted: 2013-04-27 tags: 60-minutes-or-less time-to-make …. How to use a variational Autoencoder to augment tabular data. For example, we have load_wine() and load_diabetes() defined in similar fashion. fit(X_train, y_train) #Predict the response for test dataset …. I chose the wine dataset because it is great for a beginner. To have everything in one DataFrame, you can concatenate the features and the target into one numpy array with np. 2 does not have load_titanic either. It’s available in Scikit-Learn. The k-means clustering method is an unsupervised machine learning technique used to identify clusters of data objects in a dataset. Точно так же при распознавании вина мы вызовем load_wine(). The following command can be used for accessing the value of above: 1. # import scikit-learn dataset library from sklearn import datasets # load dataset dataset = datasets. Question: In Python upload the Wine database (sklearn. Wine¶ The wine dataset contains data from chemical analysis on 178 wines of three classes. FutureWarning) Target looks like classification Linear Discriminant Analysis training set score: 1. ) In [1]: import numpy as np import pandas as pd from sklearn. Code: In the following code, we will import loguniform from sklearn…. Principal component analysis, or PCA, is a dimensionality reduction technique for Unsupervised Learning. Here you can build a model to classify the type of wine. Load the scikit-learn's Wine recognition dataset; separate 20% data as test data set; predict the wine …. pyplot as plt # Preprocessing from sklearn. The simplest kind of linear regression involves taking a set …. Principal component analysis is a technique used to reduce the dimensionality of a data set. We usually let the test set be 20% of the entire data set …. The Cleveland Heart Disease Dataset…. Decision tree algorithms work by constructing a “tree. These datasets are Iris, Breast Cancer, and Wine datasets from Sklearn. Each observation has two inputs and 0, 1, or 2 class values. a Scikit Learn) library of Python. 加载 sklearn 自带红酒数据集(wine)。 检测其中的异常值(判断标准:与平均值的偏差 超过 3 倍标准差的数值)。 提示:用数据生成 pandas 的 DataFrame 对象(建议放入数据集 本身的特征名),以便用 pandas 的相关函数来实现。 附上源代码:. 计算机生成的数据集(Generated Dataset):sklearn. make_imbalance turns an original dataset into an imbalanced dataset. CORD-19 is a corpus of academic papers about COVID-19 and related coronavirus research, curated and maintained by the Semantic Figure 01: bar chart for quality levels lipidr an easy-to-use R package implementing a complete workflow for downstream analysis of targeted and untargeted lipidomics data Two example datasets…. Removing this from the original dataset …. You can easily use: import seaborn as sns titanic=sns. When data is uploaded into the datastore …. Pandas is a tool used for data wrangling and analysis. 实训1 使用 sklearn处理wine和wine_quality数据集 1. org 下载的数据 从外部加载的数据 用的比较多的就是1和3,这里进行主要介绍,其他的会进行简单介绍,但是不建议使用。 玩具数据集 scikit-learn 内置有一些小型标准数据集,不需要从某个外部网站下载任何文件,用datasets. Steps for K-fold cross-validation ¶. Loading method: Dataset= sklearn. (KFold 는 생략하고 straitifiedkfold로 바로 설명하겠습니다. Scikit-learn Datasets Scikit-learn, a machine learning toolkit in Python, offers a number of datasets ready to use for learning ML and developing new methodologies. First of all, before processing algorithms, we have to import some libraries and read a file with the help of pandas. If you are new to sklearn, it may be little harder to wrap your head around knowing the available datasets, what information is available as part of the dataset and how to access the datasets. The scikit-learn library is splitting the data into a training and testing. A decision tree is a simple representation for classifying examples. By using the UCI Machine Learning Repository, you acknowledge and accept the cookies and privacy practices used …. model_selection import train_test_split X_train, X_test. Wine dataset model development and evaluation Published at Mar 31, 2022. LDA in Python: LDA is a very simple and popular algorithm in practice. load_boston (*, return_X_y=False) 已弃用:load_boston 在 1. (8 days ago) Create A Binary Classification Dataset Python Sklearn Datasets Make Classifica All Time Past 24 Hours Past Week Past month All: 31 Courses Beginner Intermediate Advanced Submit Courses Sklearn. Available Data Sets in Sklearn; Artificial Datasets with Scikit-Learn; Train and Test Sets by Splitting Learn and Test Data; k-Nearest Neighbor Classifier in Python; k-Nearest-Neighbor Classifier with sklearn; Therefore, we use the UCI wine dataset …. We will first cover an overview of what is random forest and how it works and then implement an end-to-end project with a dataset …. In the dataset, the inputs (X) consist of 13 features relating to various properties of each wine type. load_breast_cancer (\*[, return_X_y, as_frame]) Load and return the breast cancer wisconsin dataset (classification). model_selection import train_test_split from sklearn…. load_wine(*, return_X_y= False, as_frame= False) 加载并返回葡萄酒数据集(分类)。 版本0. from sklearn import datasets from sklearn GradientBoostingClassifier estimator class can be upgraded to LightGBM by Let's get started NF with deployment using databricks on AWS preprocessing The H2O Python Module sklearn precomputed kernel example datasets import load_wine import neptune from datasets import load_wine …. For fitting our model I have used sklearn. If passing a column name, use a keyword. the Wine dataset, the dataset contains 13 features which reflect which class of wine a certain data point is. Dataset Loading Utilities. ‫العربية‬ ‪Deutsch‬ ‪English‬ ‪Español (España)‬ ‪Español (Latinoamérica)‬ ‪Français‬ ‪Italiano‬ ‪日本語‬ ‪한국어‬ ‪Nederlands‬ Polski‬ …. The repository has two datasets related to red and white variants of the Portuguese "Vinho Verde" wine…. Let us first select the dataset and then proceed with the model. 1 scikit-learn refresher KNN classification. Today, we learned how to split a CSV or a dataset into two subsets- the training set and the test set in Python Machine Learning. Most objects for classification that mimick the scikit-learn estimator API should be compatible with the plot_decision_regions function. Outlier Detection DataSets (ODDS) In ODDS, we openly provide access to a large collection of outlier detection datasets with ground truth (if available). How to split your dataset to train and test datasets using. The target variable is the wine class, and so we will use it for classification tasks. internet-advertisements dataset. Wine certi cation and quality assessment are key elements within this. We will use a white wine dataset, public available at the UCI Machine Learning Repository: Wine Quality, for this project. 下面对 Sklearn 自带的"红酒数据集"进行 KNN 算法 分类预测。最终实现向训练好的模型喂入数据,输出相应的红酒类别,示例代码如下: #加载红酒数据集 from sklearn. sklearn에 있는 연습용 dataset 본문 Load and return the wine dataset (classification). ) spi on Jan 11, 2019 Perhaps more …. 加载 sklearn 自带红酒数据集(wine)。检测其中的异常值. Principal component Analysis(PCA) Part1. The problem that we are going to solve is to predict the quality of wine based on 12 attributes. _wine_dataset: Wine recognition dataset . We will attempt to predict quality to a >90% accuracy after rounding our predictions. 1 Data Link: Enron email dataset…. Looks like, k=3 performed best for this dataset …. pyplot as plt import numpy as np from sklearn. Python’s Sklearn library provides a great sample dataset generator which will help you to create your own custom dataset. import pandas as pd from sklearn import datasets wine = datasets Actually It mainly contains the data for image recognization Since we want to …. discriminant_analysis import LinearDiscriminantAnalysis from sklearn import datasets …. It is available through sklearn. datasets import load_wine wine=load_wine() #Conver to pandas dataframe data=pd. data missing_data, full_data = create_data(data) h5_file = …. from sklearn import datasets from yellowbrick. Visual interface for loading datasets in RStudio from all installed (including unloaded) packages, also includes …. 그러면 우선 파이썬으로 load_wine을 이용해서 와인 분류를 예측해보도록 하겠다. datasets import load_iris import pandas as pd dataset = load_iris() df = pd. The goal is, therefore, to identify which features are the provided by sklearn. Let’s say you are interested in the samples 10, 80, and 140, and want …. linear_model import LogisticRegression import sklearn. These texts are provided by the vintner and aim to describe the wine …. Apply up to 5 tags to help Kaggle users find your dataset. It is advised to read the description of the dataset before proceeding, will help you comprehend the problem better. Dataset name Observations Dimensions Features Targets; Boston house-prices dataset (regression) Data transformation packages are found in the sklearn…. Transcribed image text: Scikit Learn, Classification and Clustering SVM on Wine quality dataset Clustering You have already seen an example of clustering using scikit-learn in lecture. Scikit-learn (also known as sklearn) is the first association for “Machine Learning in Python”. As illustrated in Figure 1, the dataset represents chemical analyses of wines …. decomposition import PCA from sklearn…. In machine learning, we need some training data. Now after finishing importing our libraries, we load our dataset. Three types of wine are represented in the 178 samples, with the results of 13 chemical analyses recorded for each sample. model_selection import train_test_split. 查看红酒数据集中的数据 wine = load_wine() #注意这里是采用jupyter notebook环境,如果直接编写脚本会. It determines the source of wine based on different chemical parameters. Below attach source contains a file of the wine dataset so download first to proceed. Wine Recommender System Using Principal Component An…. linear_model import LogisticRegression from sklearn import metrics import seaborn as sn import matplotlib. 可在线下载的数据集(Downloaded Dataset):sklearn. ¶ Import all the necessary packages: Numpy and Pandas for Data Exploration and sklearn …. Python Examples of sklearn. #importing libraries import numpy as np from collections import Counter import pandas as pd import lightgbm as lgb from sklearn. The Boston house prices dataset is loaded using the load_boston() function: from sklearn import datasets # Load the dataset boston = datasets. import pandas as pd from sklearn. In that post, I covered how to extract the dataset from sklearn…. Invece, in altre occasioni, ti ho parlato di come importare i set del modulo sklearn. Each expert graded the wine quality. Examples Let’s say you are interested in the samples 10, 80, and 140, and want to know their class name. Here, red wine instances are present at a high rate and white wine instances are less than red. He also touches on pooled models i. linear_model import LogisticRegression from sklearn. Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with a single line of code. Wine Dataset (Classification) from sklearn. Boosting methods build ensemble …. The class labels (1, 2, 3) are listed in the first column, and the columns 2-14 correspond to the following 13 attributes (features): More information about the sklearn. In Decision Support Systems, Elsevier, 47 (4):547-553. The documentation for the red wine dataset states that the quality score is between 0 to 10 but when the data set was closely examined, there were no data points for quality scores 0,1,2,3,9,10. That’s a good sign! we got consistent results by applying both sklearn …. load_dataset (name, cache=True, data_home=None, **kws) ¶. The data used in this post is Sklearn wine data set …. LogisticRegression(로지스틱 회귀) (0) 2020. When it comes to DeepLearning, the more data we have the better the …. Split into training and test datasets. The analysis determined the quantities of 13 constituents found in each of the three types of wines. Sklearn作为Python中经典的机器学习模块,该模块围绕着机器学习提供了很多可直接调用的机器学习算法以及很多经典的数据集,本文就对sklearn中专门用来得到已有或自定义数据集的datasets模块进行详细介绍(datasets …. Use chemical analysis data to determine the origin of wines grown in the same region. Logistic Regression Using Python (scikitlearn) By. Scikit-learn’s datasets module provides 7 built-in toy datasets …. Wine dataset; The table below summarizes the properties of these datasets. In case, you don’t want to explicitly assign column name, you could use the following commands: 1. Exploring OLS, Lasso and Random Forest in a regression task. datasets 라이브러리를 이용하여 캘리포니아 데이터셋을 불러온다. 下面使用决策树算法对 Sklearn 库中的红酒数据进行模型训练,与数据预测,示例代码如下:. # scatter matrix of wine data set import pandas as pd from sklearn import datasets wine = datasets. For minimizing non convex loss functions (e. We also have reviews from beeradvocate and ratebeer. 이 데이터셋은 총 3개의 클래스를 가지며, 각 59, 71, 48개의 샘플 데이터를 가지고 . Half of these wines are red wines, and the other half are white. Following are the types of samples it provides. PCA is typically employed prior to implementing a machine learning algorithm because it minimizes the number of variables used to explain the maximum amount of variance for a given data set. org/stable/modules/generated/sklearn. datasets and convert it into pandas dataframe. model_selection import train_test_split 2. shape) 2 自定义数据集 前面我们介绍了几种datasets自带的经典数据集,但有些时候我们需要自定义生成服从某些分布或者某些形状的数据集,而datasets中就提供了这样的一些方法: 2. Here, we are going to use the Iris Plants Dataset …. First, here's some code that we won't use Scikit-Learn makes data preprocessing a breeze. ensemble import RandomForestClassifier from sklearn. load_sample_image用法及代碼示例; Python sklearn. The first part of this tutorial post goes over a toy dataset (digits dataset) to show quickly illustrate scikit-learn’s 4 step modeling pattern and show the behavior of the logistic regression algorthm. datasets import load_wine #KNN分类算法 from sklearn. The example below generates a 2D dataset of samples with three blobs as a multi-class classification prediction problem. The decision tree algorithm breaks down a dataset …. The output is a fully self-contained HTML application. You’ve loaded a dataset into a Pandas dataframe, that’s ready to be explored and used. csv') So, when you load the dataset …. Notice that the coefficients captured in this table (highlighted in red) match with the coefficients generated by sklearn. # generate 2d classification dataset X, y = make_blobs (n_samples=100, centers=3, n_features=2) 1. cluster import KMeans # Get the dataset of wine . wine grape in English Bibliographic References Aronsson, Mora (2004) Thomas Karlssons Kärlväxtlista. use ('ggplot') iris = datasets. load_iris用法及代碼示例; Python sklearn. データが複数のガウス分布から生成されたとみなし、どのガウス分布に属するかで分類する手法。. For more details, consult: or the reference [Cortez et al. However, you should be a bit cautious about using cross-validation with large datasets …. load_iris() >>> digits = datasets. The details are described in [Cortez et al. In Scikit-Learn, every class of model is represented by a Python class. Tune model using cross-validation pipeline. We can visualize the relationship between abv and wine type in the entire dataset with the following code: # plot the relationship between wine type and alcohol by volume # red wines appear to have higher abv overall abv_winetype = sns. model_selection import train_test_split import matplotlib. Digits Dataset - It has images of size 8x8 of digits 0-9. There are two datasets related to red and white vinho verde wine samples Portugal North. import numpy as np import pandas as pd from sklearn. Average prices are calculated from a 'topped and tailed' data set…. Wine Data Database ===== Notes ----- Data Set Characteristics: :Number of Instances: 178 (50 in each of three classes) :Number of Attributes: 13 numeric, predictive attributes and the class :Attribute Information: - 1) Alcohol - 2) Malic acid - 3) Ash - 4) Alcalinity of ash - 5) Magnesium - 6) Total phenols - 7) Flavanoids - 8) Nonflavanoid phenols - 9) Proanthocyanins - 10)Color intensity - 11)Hue - 12)OD280/OD315 of diluted wines …. datasets import load_wine wine = load_wine(as_frame=True). k means clustering on csv file python github. · Digits– Classification Problem — 5620 image data with 64 features. We are going to make use of the wine dataset already present in the library. Transcribed image text: In Scikit-Learn sklearn. ) on diverse product categories. Using the SVM library of scikit-learn: . Step 1 – Load the data and get its shape (number of rows and columns) from sklearn import datasets. This blog post will help you to preprocess your data just in few minutes using Sklearn-Pandas package. scikit-learn Toy Datasets in Python: Wine recognition dataset. sklearn提供了许多包来进行机器学习,只是很多不去了解的话,到使用的时候就会手忙脚乱根本不会 …. A dataset, or data set, is simply a collection of data. neighbors import KNeighborsClassifier #分割训练集与测试集 from sklearn. barplot (x='quality',y='citric acid',data=wine…. The following are 16 code examples for showing how to use sklearn. All wines are produced in a particular area of Portugal. Load wine dataset; Split the data into train and test. LogisticRegression(로지스틱 회귀) 2020. modulenotfounderror: no module named 'sklearn' spyder; scikitlearn install; no module named sklearn in jupyter notebook; install sklearn. Exploratory Data Analysis (EDA) is an important and recommended first step of Machine Learning (prior to the training of a …. loads the iris dataset using sklearn (sklearn. The predictors are all numeric and detail each wine’s chemical makeup. there is no data about grape types, wine brand, wine …. It is a supervised machine learning technique where the data is continuously split according to a certain parameter. load_wine (as_frame=True) wine = data. The wine dataset contains the results of a chemical analysis of wines …. The last column is the label (the number written). GridSearch and RandomSearch are common techniques for hyperparameter tuning. Now that we have loaded a toy dataset from sklearn API by applying the function load_wine(), we store it inside the variable wine Image by Author Next, let’s make use of shape in order to. wine=load_wine() We can now check the sample data and shape of the data present in wine bunch object using wine. This data is the result of a chemical analysis of wines grown in the same region in Italy using three different cultivars. I will use a simple wine quality dataset from the UCI repository. 1、 Sklearn introduction Scikit learn is a machine learning library developed by Python language, which is generally referred to as sklearn. pyplot as plt import seaborn as sns from sklearn import datasets wine = datasets. load_wine(*, return_X_y=False, as_frame=False) [source] ¶. xTrain, xTest, yTrain, yTest = train_test_split (x, y, test_size = 0. load_boston() This returns a ‘Bunch’ object with the following keys: Key Description; DESCR: Description of the dataset…. I will be using sklearn’s PCA methods (dimension reduction), K-mean methods (clustering data points) and one of their built-in datasets …. Code: from sklearn import datasets from sklearn. pyplot as plt import seaborn as sns import pandas as pd import numpy as np. Each wine in this dataset is given a “quality” score between 0 and 10. Grid search is the hyperparameter optimization technique. datasets has load_wine loader: 1. There are two datasets related to red and white vinho verde wine …. sklearn - short for scikit-learn, a machine learning toolkit in Python [ ] [ ] import numpy as np import pandas as pd import We'll use sklearn's StandardScaler to z-score the features of the wine dataset…. Read the data using pandas into a dataframe. In the above reference, two datasets were created, using red and white wine samples. REGRESSION is a dataset directory which contains test data for linear regression. The dataset related to red variants of the Portuguese “Vinho Verde” wine. datasets import load_breast_cancer. Visualizing trees with Sklearn. Scikit Learn, Classification and Clustering SVM on Wine quality dataset . HMDB51 (root, annotation_path, frames_per_clip, step_between_clips=1, frame_rate=None, fold=1, train=True, transform=None, _precomputed_metadata=None, num_workers=1, _video_width=0, _video_height=0, _video_min_dimension=0, _audio_samples=0) [source] ¶. Here’s a brief description of four of the benchmark datasets I often use for exploring binary classification techniques. In this case, our bunch object is “wine”. this process use in machine learning problems, Get better predictor variable In regression and classification Problem. Visualizing the Important Characteristics of a Dataset¶ Let's download the Wine dataset …. datasets import load_wine from 와인 데이터 읽기 wine = load_wine() wine. Here are the steps for building your first random forest model using Scikit-Learn: Set up your environment. Recommender Systems Datasets. feature_selection import SelectKBest, chi2, RFE from sklearn. The attributes are (dontated by Riccardo Leardi, …. This package also features helpers to fetch larger datasets …. model_selection import RepeatedStratifiedKFold from sklearn. neural_network import MLPClassifier from sklearn. These texts are provided by the vintner and aim to describe the wine in an appealing way. Complete Guide to Using AutoSklearn. Beans is a dataset of images of beans taken in the field using smartphone cameras. 아래와 같이 datasets에서 원하는 데이터셋 함수를 불러오고, 그 안에 들어있는 데이터들을 활용하면 된다. You can directly use the datasets objects from the sklearn …. In [27]: # Load Wine Dataset from sklearn wine = load_wine() # Create a dataframe from the data df = pd. Why Neural Networks? In this example we attempt to build a neural network that can classify wines from three wineries by thirteen. 1、 使用sklearn 的决策树算法对葡萄酒数据集进行 分类 ,要求: 划分 训练集和测试集(测试集占20%) 对测试集的预测类别标签和真实标签进行对比 输出 分类 的准确率 调整参数比较不同算法(ID3,C4. 70+ Machine Learning Datasets & Project Ideas – Work on. org repository (note that the datasets …. Data preprocessing Dataset was already. Similarly, for the wine dataset we would use load_wine…. load_wine; load_breast_cancer() 癌の診断結果(30項目)を入力データとして良性の癌か悪性の癌かを予測します。 用途:分類(2クラス) データ件数:569; データ次元数:30; ドキュメント:sklearn. The attributes in this dataset are: Standardizing the dataset. sklearn の中には、機械学習やデータ解析に使えるデータセット …. manifold import TSNE from sklearn…. linear_model import LinearRegression from sklearn import metrics import matplotlib. The dataset is available in the scikit-learn library. Welcome to the data repository for the Python Programming Course by Kirill Eremenko. wine_data: A 3-class wine dataset for classification. Sulphates: Amount of sulfur dioxide gas (S02) levels in the wine; Alcohol: Amount of alcohol present in the wine; Quality: Final quality of the wine mentioned; 2. In [ ]: #Import knearest neighbors Classifier model from sklearn. load_wine使用的例子?那麽恭喜您, 這裏精選的方法代碼示例或許可以為您提供幫助。. Yelp Open Dataset An all-purpose dataset for learning. 사이킷런(scikit-learn / sklearn) - wine datasets with kfold¶ 이번 포스팅에서는 wine 데이터셋을 살펴보겠습니다. #Import scikit-learn dataset library from sklearn . 사이킷런 (scikit-learn / sklearn) - wine datasets with kfold. Обучение на датесете из sklearn. Our dataset can be loaded by calling “load_()” and creating a bunch object. Now that you have two of the arrays loaded, you can split them into testing and training data using the test_train_split() function:. In this article, I will share the three major techniques of Feature Selection in Machine Learning with Python. You can also input your model, whichever library it may be from; could be Keras, sklearn…. preprocessing import PolynomialFeatures: poly_reg = …. KFold class has split method which requires a dataset …. datasets module provide a few toy datasets (already-vectorized, in Numpy format) that can be used for debugging a model or creating simple code examples. The module sklearn comes with some datasets.