Abalone Dataset,也称为鲍鱼数据集,是一个经典的机器学习数据集,主要用于回归和分类任务的实践。它最初来源于UCI机器学习库,由typeid.com网站收集。这个数据集源自对加州海岸常见的几种鲍鱼物种(主要是Haliotis species)的生物学特性研究。 数据集包含以下特征: 1. Rings: 鲍鱼壳上的螺旋纹数量,可以作为一个年龄指标...
AbaloneDataSet(鲍鱼数据集)
importpandas as pd # Load the dataset url ="https://archive.ics.uci.edu/ml/machine-learning-databases/abalone/abalone.data" column_names = ["Sex","Length","Diameter","Height","WholeWeight","ShuckedWeight","VisceraWeight","ShellWeight","Rings"] data = pd.read_csv(url, names=column_na...
abalone set鲍鱼数据集 Set鲍鱼数据集鲍鱼数据集 AbaloneDataSet Abalone数据集 dataset 《Abalone Data Set(鲍鱼数据集).pdf》由会员分享,可在线阅读,更多相关《Abalone Data Set(鲍鱼数据集).pdf(9页珍藏版)》请在人人文库网上搜索。 Abalone Data Set 鲍鱼数据集鲍鱼数据集 数据摘要 数据摘要 Predict the age of...
i tried to use the abalone example but it's not running in the google collab from ucimlrepo import fetch_ucirepo # fetch dataset abalone = fetch_ucirepo(id=1) # data (as pandas dataframes) X = abalone.data.features y = abalone.data.targe...
鲍鱼数据集abalone-dataset 鲍鱼数据集abalone-dataset 上传者:2301_78286654时间:2024-03-30 abalone:鲍鱼数据集的数据分析 鲍鱼 鲍鱼数据集的数据分析。 上传者:weixin_42171208时间:2021-04-27 Abalone Data Set.rar( 数据挖掘 数据集 ) Abalone Data Set.rar( 数据挖掘 数据集 ) ...
(Cox, 1962;Hansen, 1970). The boring yellow sponge,Clionasp., grows on the shells and secretes an acid, creating pits. Using a large dataset (n=786) quantifying infestation byClionaand abalone growth, Morejohn was able to show that heavily infected abalone were always the largest individuals...
Forty-nine SNP markers developed from the genome dataset of Pacific abalone (Haliotis discus hannai) and their application in population genetic analysisPacific abaloneHaliotis discus hannaiSingle nucleotide polymorphism (SNP)Marker developmentThe SNP markers for Pacific abalone (...
The initial dataset consisted of 7 continuous predictors and a single categorical predictor. The 7 continuous predictors were found to be highly correlated, so I thought it would be a useful simplification to reduce the number of predictors. Three of the predictors were some length scale while the...
Addition of variables: We will update the abalone dataset to create new variable named Infant which will have values based on original value from Sex variable. It will have value of I, when Sex variable is I and NI otherwise. abalone['Infant'] <- ifelse(abalone$Sex == 'I','I','NI...