From e1dfe424cc1a76b53aa86bf14a46d22b6acfa2d8 Mon Sep 17 00:00:00 2001 From: Isabelapaulacassettari <69772422+Isabelapaulacassettari@users.noreply.github.com> Date: Wed, 19 Aug 2020 13:34:21 -0300 Subject: [PATCH 1/2] Update sklearn_transformers.py --- .../sklearn_transformers.py | 49 ++++++++++++++++++- 1 file changed, 48 insertions(+), 1 deletion(-) diff --git a/my_custom_sklearn_transforms/sklearn_transformers.py b/my_custom_sklearn_transforms/sklearn_transformers.py index e88e9a7c..370709a0 100644 --- a/my_custom_sklearn_transforms/sklearn_transformers.py +++ b/my_custom_sklearn_transforms/sklearn_transformers.py @@ -13,4 +13,51 @@ def transform(self, X): # Primeiro realizamos a cópia do dataframe 'X' de entrada data = X.copy() # Retornamos um novo dataframe sem as colunas indesejadas - return data.drop(labels=self.columns, axis='columns') + return data.drop(labels=self.columns, axis='columns') def __init__(self, clusterer, classifier): + self.clusterer = clusterer + self.classifier = classifier +def predict(self, X): + return self.classifier_.predict(X) +def decision_function(self, X): + return self.classifier_.decision_function(X) +def plot_scatter(X, color, alpha=0.5): + return plt.scatter(X[:, 0], + X[:, 1], + c=color, + alpha=alpha, + edgecolor='k') +X, y = make_blobs(n_samples=N_SAMPLES, + cluster_std=[1.0, 1.0, 0.5], + centers=[(-5, -5), (0, 0), (5, 5)], + random_state=RANDOM_STATE) +lusterer = AgglomerativeClustering(n_clusters=3) +cluster_labels = clusterer.fit_predict(X) + +plt.figure(figsize=(12, 4)) + +plt.subplot(131) +plot_scatter(X, cluster_labels) +plt.title("Ward Linkage") +X_new, y_new = make_blobs(n_samples=10, + centers=[(-7, -1), (-2, 4), (3, 6)], + random_state=RANDOM_STATE) +plot_scatter(X, cluster_labels) +plot_scatter(X_new, 'black', 1) +plt.title("Unknown instances") +classifier = RandomForestClassifier(random_state=RANDOM_STATE) +inductive_learner = InductiveClusterer(clusterer, classifier).fit(X) + +probable_clusters = inductive_learner.predict(X_new) +plot_scatter(X, cluster_labels) +plot_scatter(X_new, probable_clusters) +x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1 +y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1 +xx, yy = np.meshgrid(np.arange(x_min, x_max, 0.1), + np.arange(y_min, y_max, 0.1)) +Z = inductive_learner.predict(np.c_[xx.ravel(), yy.ravel()]) +Z = Z.reshape(xx.shape) + +plt.contourf(xx, yy, Z, alpha=0.4) +plt.title("Classify unknown instances") + +plt.show() From f6aab1849fa5a1ae12982440d5e08794087975e4 Mon Sep 17 00:00:00 2001 From: Isabelapaulacassettari <69772422+Isabelapaulacassettari@users.noreply.github.com> Date: Wed, 19 Aug 2020 13:53:15 -0300 Subject: [PATCH 2/2] Rename sklearn_transformers.py to isa --- my_custom_sklearn_transforms/{sklearn_transformers.py => isa} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename my_custom_sklearn_transforms/{sklearn_transformers.py => isa} (100%) diff --git a/my_custom_sklearn_transforms/sklearn_transformers.py b/my_custom_sklearn_transforms/isa similarity index 100% rename from my_custom_sklearn_transforms/sklearn_transformers.py rename to my_custom_sklearn_transforms/isa