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Nuked Linly's splitting in mining_hq.py

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Weaponised Autism
2023-05-15 20:20:01 +03:00
parent 64fc005bfc
commit 29d1e75817
1 changed files with 0 additions and 23 deletions
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dwarves/mining_hq.py
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@@ -127,26 +127,3 @@ print(sample_rows.head())
scout.dissimilarity(sample_rows) scout.dissimilarity(sample_rows)
scout.similarity(sample_rows) scout.similarity(sample_rows)
# split the data set
gammas_train, gammas_test = train_test_split(gammas, test_size=0.20, random_state=69)
gammas_train.to_csv("datasets/videogames/games_train.csv", index=False)
gammas_test.to_csv("datasets/videogames/games_test.csv", index=False)
# kmeans pls
gammas_train_kmeans = KMeans(n_clusters=10, random_state=420, n_init="auto").fit(
gammas_train[["Critic_Score", "User_Score", "Total_Shipped"]]
)
gammas_labels = gammas_train_kmeans.labels_
silh_score = metrics.silhouette_score(
gammas_train[["Critic_Score", "User_Score", "Total_Shipped"]],
gammas_labels,
metric="euclidean",
)
print(silh_score)
gammas_train["Kmean Labels"] = gammas_labels
print(gammas_train.head())
# Naive based
gnb = GaussianNB()
prediction = gnb.fit(gammas_train)