hasil klasifikasi: k-nn tanpa n-gram, knn&unigram, knn&bigram , knn&trigram (seperti dilampiran foto)
output berupa hasil pengujian klasifikasi (akurasi, presisi, recall dan f1-score)
tools : jpyter notebook (python)
Membuatkan kodingan untuk tgs akhir dg judul analisis sentimen dengan metode K-nearest neighbor dan ekstraksi fitur N-Gram
membandingkan k-nn dan N-Gram (unigram, bigram, trigram)
Data Analysis Data Mining Machine Learning Data Science
Published Budget:
Rp 300,000 - 500,000
Finish Days: 3
Published Date: 31/03/2022 05:58:40 WIB
Start Date: 01/04/2022 10:18:41 WIB
Finish Date: 02/04/2022 21:51:42 WIB
Finish Days: 3
Published Date: 31/03/2022 05:58:40 WIB
Start Date: 01/04/2022 10:18:41 WIB
Finish Date: 02/04/2022 21:51:42 WIB
Project Status:
Closed
Accepted Worker: zikrullah (zikrullah)
Accepted Budget: Rp 450,000
Project Ending: Completed
Accepted Worker: zikrullah (zikrullah)
Accepted Budget: Rp 450,000
Project Ending: Completed
Project Owner
Mantap nemuin worker sesuai bidang data science, pengerjaan cepat tepat sesuai request.
Accepted Worker
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