Mobile Phone Clasification Menggunakan Metode Random Forest, Decission Tree, dan Support Vector Machine dengan Optimasi Parameter Tunning (DI ZENIUSACCELERATED MACHINE LEARNING PROGRAM)

Niam, M. Zaim Husnun (2022) Mobile Phone Clasification Menggunakan Metode Random Forest, Decission Tree, dan Support Vector Machine dengan Optimasi Parameter Tunning (DI ZENIUSACCELERATED MACHINE LEARNING PROGRAM). Project Report. [s.n.], [s.l.]. (Unpublished)

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Abstract

Laporan Kerja Praktik yang bersumber dari Studi Independen Kampus Merdeka dengan program Accelerated Machine Learning. Menggunakan metode statistik Random Forest, Decision Tree, dan Support Vector Machine untuk mengklasifikasikan harga mobile phone

Item Type:	Monograph (Project Report)
Uncontrolled Keywords:	Machine learning, Metode Random Forest, Decission Tree, Support Vector Machine
Subjects:	C Auxiliary Sciences of History > C Auxiliary sciences of history (General) L Education > L Education (General) L Education > LB Theory and practice of education Q Science > Q Science (General) > Q325.5 Machine learning. Support vector machines.
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	M. Zaim Husnun Niam
Date Deposited:	12 Dec 2022 02:23
Last Modified:	12 Dec 2022 02:23
URI:	http://repository.its.ac.id/id/eprint/95209

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