The Experts below are selected from a list of 39 Experts worldwide ranked by ideXlab platform
Hugh D. Wilson - One of the best experts on this subject based on the ideXlab platform.
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Iris Virginica (Native)
2011Co-Authors: Hugh D. WilsonAbstract:Iris Virginica, Flower. Family Iridaceae, Subclass Liliidae. Origin: Native
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Iris Virginica (Native) 2
2011Co-Authors: Hugh D. WilsonAbstract:Iris Virginica, Flower - close. Family Iridaceae, Subclass Liliidae. Origin: Native
James R. Manhart - One of the best experts on this subject based on the ideXlab platform.
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Iris Virginica (Native) 4
2011Co-Authors: James R. ManhartAbstract:Iris Virginica, flower. Family Iridaceae, Subclass Liliidae. Origin: Native
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Iris Virginica (Native) 3
2011Co-Authors: James R. ManhartAbstract:Iris Virginica, whole plant. Family Iridaceae, Subclass Liliidae. Origin: Native
Michael Marshall - One of the best experts on this subject based on the ideXlab platform.
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Iris_sklearn
2018Co-Authors: Michael MarshallAbstract:Iris plants dataset 4 numeric, predictive attributes and the class sepal length in cm sepal width in cm petal length in cm petal width in cm class: Iris-Setosa Iris-Versicolour Iris-Virginica
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Scikit-Learn Iris
2018Co-Authors: Michael MarshallAbstract:Data Set Characteristics: Number of Instances: 150 (50 in each of three classes) Number of Attributes: 4 numeric, predictive attributes and the class Attribute Information: sepal length in cm sepal width in cm petal length in cm petal width in cm class: Iris-Setosa Iris-Versicolour Iris-Virginica
Rafikasari, Elok Fitriani - One of the best experts on this subject based on the ideXlab platform.
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PERBANDINGAN METODE ANALISIS DISKRIMINAN, NEURAL NETWORK, DISKRIMINAN KERNEL, REGRESI LOGISTIC, MARS UNTUK DATA BANGKITAN (KOMBINASI VARIANS, OVERLAP DAN KORELASI)
'LPSDI Bina Patria', 2019Co-Authors: Nariswari Rinda, Rafikasari, Elok FitrianiAbstract:Metode untuk pengklasifikasian data diantaranya menggunakan analisis diskriminan, analisis diskriminan kernel, analisis regresi logistik, neural network, dan MARS. Secara keseluruhan masing-masing metode jika diterapkan pada data mempunyai kelebihan maupun kekurangan. Pada pengelompokan data Iris Virginica dan vercicolor, metode MARS dan NN FeedForward paling baik digunakan. Sedangkan pada pengelompokan data Iris setosa dan vercicolor, metode Analisis Diskriminan, NN RBF dan NN FeedForward adalah metode yang paling baik digunakan dalam pengelompokan. Namun berbeda dengan hasil analisis data simulasi yang dibangkitkan melalui Minitab, metode MARS adalah satu-satunya metode yang paling baik digunakan untuk data simulasi karena mempunyai rata-rata ketepatan klasifikasi yang paling besar diantara metode lainnya
Kenneth Lange - One of the best experts on this subject based on the ideXlab platform.
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Effects of the parameters k and ϕ on cluster paths in the Iris data.
2015Co-Authors: Gary K. Chen, Eric C. Chi, John Michael O. Ranola, Kenneth LangeAbstract:Black, red, and green points denote the species Iris-setosa, Iris-versicolor, and Iris-Virginica, respectively. These points are projections of the Iris dataset on the first two principal components (PCs). Lines trace the cluster centers as they traverse the regularization path. The subtle impact of ϕ is revealed in two cases. At k = 50, a red dot coalesces with the right cluster at ϕ = 0, but with the left cluster for larger values of ϕ. At k = 5 or k = 10, the two green dots at the extreme lower left corner coalesce later at the largest value of ϕ.
