scikit learn - Binary vectors as y_score argument of roc_curve -


स्केलन आरओसीकार्व राज्यों:

"y_score: सरणी, आकृति = [एन_एसम्प्ले] लक्ष्य स्कोर, कर सकते हैं या तो सकारात्मक वर्ग, आत्मविश्वास मानों, या द्विआधारी निर्णयों की संभावना अनुमान है। "

किस स्थिति में यह एक द्विआधारी सदिश (" बाइनरी फैसले ") को y_score सेट करने का अर्थ रखेगा? क्या उस पर एक बिंदु के साथ एक आरओसी की अवस्था का परिणाम नहीं होगा, जिस तरह से किस तरह से इस बिंदु को खारिज कर दिया?

यदि आप एक क्लासिफायरियर का उपयोग कर रहे हैं जो आउटपुट संभाव्यता स्कोर (जैसे svm.SVC बिना स्पष्ट probability = True ) नहीं करता है, तो एक आरओसी वक्र की गणना करने का कोई तरीका नहीं है । एपीआई डिजाइनर के रूप में, आपके पास दो विकल्प हैं: एक अपवाद बढ़ाएं और उपयोगकर्ता को कोई उपयोगी जानकारी नहीं प्रदान करें, या एक डेटा बिन्दु के साथ वक्रित वक्र का साजिश करें। मैं बहस होगा बाद में अधिक उपयोगी है।

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