Star

A 6 class star dataset for star classification with Deep Learned approaches

Probabilistic distance clustering (PD-clustering) is an iterative, distribution free, probabilistic clustering method. PD-clustering assigns units to a cluster according to their probability of membership, under the constraint that the product of the probability and the distance of each point to any cluster centre is a constant. PD-clustering is a flexible method that can be used with non-spherical clusters, outliers, or noisy data. PDQ is an extension of the algorithm for clusters of different size. GPDC and TPDC uses a dissimilarity measure based on densities. Factor PD-clustering (FPDC) is a factor clustering method that involves a linear transformation of variables and a cluster optimizing the PD-clustering criterion. It works on high dimensional data sets.

Cristina Tortora

FPDclustering

PD-Clustering and Related Methods

Star function

A data frame with 202 observations and 13 variable.<dl>
<dt>K</dt>
<dd>Absolute Temperature (in K)</dd><dt>Lum</dt>
<dd>Relative Luminosity (L/Lo)</dd><dt>Rad</dt>
<dd>Relative Radius (R/Ro)</dd><dt>Mag</dt>
<dd>Absolute Magnitude (Mv)</dd><dt>Col</dt>
<dd>Star Color (white,Red,Blue,Yellow,yellow-orange etc)</dd><dt>Spect</dt>
<dd>Spectral Class (O,B,A,F,G,K,,M)</dd><dt>Type</dt>
<dd>Star Type (Red Dwarf, Brown Dwarf, White Dwarf, Main Sequence , SuperGiants, HyperGiants)</dd>
</dl>

Format

Star dataset to predict star types
 — Star

A data frame with 202 observations and 13 variable.<dl>
<dt>K</dt>
<dd>Absolute Temperature (in K)</dd>

<dt>Lum</dt>
<dd>Relative Luminosity (L/Lo)</dd>

<dt>Rad</dt>
<dd>Relative Radius (R/Ro)</dd>

<dt>Mag</dt>
<dd>Absolute Magnitude (Mv)</dd>

<dt>Col</dt>
<dd>Star Color (white,Red,Blue,Yellow,yellow-orange etc)</dd>

<dt>Spect</dt>
<dd>Spectral Class (O,B,A,F,G,K,,M)</dd>

<dt>Type</dt>
<dd>Star Type (Red Dwarf, Brown Dwarf, White Dwarf, Main Sequence , SuperGiants, HyperGiants)</dd>


</dl>

Star: Star dataset to predict star types

Description

Usage

Arguments

Format

Examples