Title:
Kode-Program-Algoritma-Nearest-Neighbor
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Description: In pattern recognition, the k-nearest neighbor algorithm (k-NN) is a method for classifying objects based on closest training examples in the feature space. k-NN is a type of instance-based learning, or lazy learning where the function is only approximated locally and all computation is deferred until classification. The k-nearest neighbor algorithm is amongst the simplest of all machine learning algorithms: an object is classified by a majority vote of its neighbors, with the object being assigned to the class most common amongst its k nearest neighbors (k is a positive integer, typically small). If k = 1, then the object is simply assigned to the class of its nearest neighbor.
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Similarity.~dpr
Similarity.cfg
Similarity.dof
Similarity.dpr
Similarity.exe
SIMILARITY.GDB
Similarity.res
UDM.~ddp
UDM.~dfm
UDM.~pas
UDM.dcu
UDM.ddp
UDM.dfm
UDM.pas
UInputKasus.~ddp
UInputKasus.~dfm
UInputKasus.~pas
UInputKasus.dcu
UInputKasus.ddp
UInputKasus.dfm
UInputKasus.pas
UKasus.~dfm
UKasus.~pas
UKasus.dcu
UKasus.dfm
UKasus.pas
UNilaiVariabel.~ddp
UNilaiVariabel.~dfm
UNilaiVariabel.~pas
UNilaiVariabel.dcu
UNilaiVariabel.ddp
UNilaiVariabel.dfm
UNilaiVariabel.pas
USettingAtribut.~ddp
USettingAtribut.~dfm
USettingAtribut.~pas
USettingAtribut.dcu
USettingAtribut.ddp
USettingAtribut.dfm
USettingAtribut.pas
UTesting.~ddp
UTesting.~dfm
UTesting.~pas
UTesting.dcu
UTesting.ddp
UTesting.dfm
UTesting.pas
UUtama.~ddp
UUtama.~dfm
UUtama.~pas
UUtama.dcu
UUtama.ddp
UUtama.dfm
UUtama.pas
