The most commonly reported measure of classifier performance is accuracy: the percent of correct classifi ions obtained. This metric has the advantage of being easy to understand and makes comparison of the performance of different classifiers trivial, but it ignores many of the factors which should be taken into account when honestly assessing the performance of a classifier.
classifying machine in mining production high quality. Mining and amp; Construction Machinery. Excavators, haul trucks, foresters, valves, regulators, construction and mining machinery must guarantee precision and optimal performance.
from sklearn.externals import joblib joblib.dump clf, "wine quality clf.pkl" When you need the classifier, it can simply be loaded using joblib and the feature array will be passed to get the result. clf1 = joblib.load "wine quality clf.pkl" clf1.predict X test 0 Congrats Now you are ready to design a deployable machine learning model. :-D
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appropriate mining method is to compare the economic efficiency of extraction of the deposit by surface and underground mining methods . This section reviews surface mining methods and practices. 1.1. Classifi ion of Surface Mining Methods Extraction of mineral or energy resources by operations exclusively involving personnel
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Classifying a test record is straightforward once a decision tree has been constructed. Starting from the root node, we apply the test condition to the record and follow the appropriate branch based on the outcome of the test. This will lead us either to another internal node, for which anew test condition is applied, or to a leaf node.
1 Rock mass classifi ion Introduction During the feasibility and preliminary design stages of a project, when very little detailed information is available on the rock mass and its stress and hydrologic characteristics, the