Step 1: Accept the number of cluste

Step 1: Accept the number of clusters to group data into and the dataset to cluster as input values

Step 2: Initialize the first K clusters
- Take first k instances or
- Take Random sampling of k elements

Step 3: Calculate the arithmetic means of each cluster formed in the dataset.

Step 4: K-means assigns each record in the dataset to only one of the initial clusters
- Each record is assigned to the nearest cluster using a measure of distance
(e.g Euclidean distance).

Step 5: K-means re-assigns each record in the dataset to the most similar cluster and re-calculates the arithmetic mean of all the clusters in the dataset.

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Hasil (Bahasa Indonesia) 1: [Salinan]

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Step 1: Accept the number of clusters to group data into and the dataset to cluster as input valuesStep 2: Initialize the first K clusters- Take first k instances or- Take Random sampling of k elementsStep 3: Calculate the arithmetic means of each cluster formed in the dataset.Step 4: K-means assigns each record in the dataset to only one of the initial clusters- Each record is assigned to the nearest cluster using a measure of distance (e.g Euclidean distance).Step 5: K-means re-assigns each record in the dataset to the most similar cluster and re-calculates the arithmetic mean of all the clusters in the dataset.

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Hasil (Bahasa Indonesia) 2:[Salinan]

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Langkah 1: Menerima jumlah cluster untuk mengelompokkan data ke dalam dan dataset untuk cluster sebagai masukan nilai Langkah 2: Inisialisasi cluster K pertama - Ambil contoh k pertama atau - Ambil sampel acak dari elemen k Langkah 3: Hitung sarana aritmatika masing-masing . klaster dibentuk pada dataset Langkah 4: K-cara memberikan setiap record dalam dataset hanya salah satu cluster awal - Setiap record ditugaskan untuk cluster terdekat menggunakan ukuran jarak (misalnya Euclidean jarak). Langkah 5: K berarti re-memberikan setiap record dalam dataset untuk cluster paling mirip dan re-menghitung mean aritmetik dari semua kelompok dalam dataset.

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Hasil (Bahasa Indonesia) 3:[Salinan]

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