query: Acceptable Accuracy, Precision, Sensitivity, and Specificity Thresholds
positive_passages.docid: 14
positive_passages.text: How to know that your machine learning problem is hopeless?
negative_passages.docid: 121031
negative_passages.text: What's the accuracy of data obtained through a random sample?
negative_passages.docid: 98770
negative_passages.text: Significant figures vs. absolute error
negative_passages.docid: 6793
negative_passages.text: A linearly independent set about approximate units
negative_passages.docid: 46938
negative_passages.text: Critical region for testing a hypothesis with exponential data.
negative_passages.docid: 16134
negative_passages.text: Determine accuracy of model which estimates probability of event
negative_passages.docid: 135987
negative_passages.text: Better accuracy with validation set than test set
negative_passages.docid: 117939
negative_passages.text: How to calculate the threshold value for numeric attributes in Quinlan's C4.5 algorithm?
negative_passages.docid: 127861
negative_passages.text: Finding Local Minima / Maxima in Noisy Data
negative_passages.docid: 109407
negative_passages.text: ROC curve and confusion matrix in classifier performance evaluation
negative_passages.docid: 10823
negative_passages.text: Is floating point arbitrary precision available?
negative_passages.docid: 9540
negative_passages.text: Output precision
negative_passages.docid: 135800
negative_passages.text: Validation of Models with Different Scale Data
negative_passages.docid: 138454
negative_passages.text: Determining sample size for ML algorithm validation
negative_passages.docid: 20531
negative_passages.text: Why is accuracy not the best measure for assessing classification models?
negative_passages.docid: 132330
negative_passages.text: Uncertainty modeling for samples
negative_passages.docid: 101939
negative_passages.text: Advantages of ROC curves