@文心快码BaiduComateuci machine learning repository: data sets 文心快码BaiduComate UCI Machine Learning Repository 介绍及数据集访问 UCI Machine Learning Repository 是什么? UCI Machine Learning Repository 是一个广泛使用的机器学习数据库,它包含了大量的数据集,这些数据集可以用于机器学习、数据挖掘、统计分析和...
curl -o data_dl.csv https://archive.ics.uci.edu/ml/machine-learning-databases/blood-transfusion/transfusion.data curl -o data_dl.csv https://archive.ics.uci.edu/ml/machine-learning-databases/blood-transfusion/transfusion.data 1. 2. 数据科学项目要获取数据的另外一种常见方式,是通过 API 进行的。
Data can be generated in .csv, ARFF or C4.5 formats. AutoUniv是一个高级数据生成器,可以用来处理分类任务。目标是反映现实数据的微妙与不同之处。数据可以在.csv中生成,采用ARFF或者C4.5的格式。 17. Bach Chorales: Time-series data based on chorales; challenge is to learn generative grammar; data...
16.AutoUniv : AutoUniv is an advanced data generator for classifications tasks. The aim is to reflect the nuances and heterogeneity of real data. Data can be generated in .csv, ARFF or C4.5 formats. AutoUniv 是一个高级数据生成器,可以用来处理分类任务。目标是反映现实数 据的微妙与不同之处。
16.AutoUniv: AutoUniv is an advanced data generator for classifications tasks. The aim is to reflect the nuances and heterogeneity of real data. Data can be generated in .csv, ARFF or C4.5 formats. AutoUniv 是一个高级数据生成器,可以用来处理分类任务。目标是反映现实数 据的微妙与不同之处。
来源: HYPERLINK mldatasets.htmlformattaskattareanumAttn mldatasets.htmlformattaskattareanumAttnumInstypesortnameUpviewlist
format=task=att=area=numAtt=numIns=type=sort=nameUpview=list 206 Data Sets Table View??List View 1. Abalone: Predict the age of abalone from physical measurements 鲍鱼DataSet:根据物理度量,预测鲍鱼的年龄。 2. Abscisic Acid Signaling Network: The objective is to determine the set of boolean ...
format=task=att=area=numAtt=numIns=type=sort=nameUpview=list 206 Data Sets Table View??List View 1. Abalone: Predict the age of abalone from physical measurements 鲍鱼DataSet:根据物理度量,预测鲍鱼的年龄。 2. Abscisic Acid Signaling Network: The objective is to determine the set of boolean ...
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The data appears already encoded and cleaned. However, by better inspecting some samples and statistics there are some observations to point out.# read input data = pd.read_csv(INPUT_PATH) data.head()IDLIMIT_BALSEXEDUCATIONMARRIAGEAGEPAY_0PAY_2PAY_3PAY_4...BILL_AMT4BILL_AMT5BILL_AMT6PAY...