Sentence examples for of maximum accuracy from inspiring English sources

Increasing the approximation orders of the Taylor's expansion the range of maximum accuracy widens.

In this work we present a new classifier developed specially for imbalanced problems, where maximum F-measure instead of maximum accuracy guide the classifier design.

GARP predictions have been shown to reach 90% of maximum accuracy using only 10 training points, with smaller incremental changes in accuracy when more data are included, such that most of the change in accuracy occurs below 20 data points [68].

This threshold is equivalent to the point on the ROC plot closest to the upper left corner and represents the point of maximum accuracy of the model.

We constructed a random forest-based classifier to distinguish these two sets using all 24 histone modifications and observed high sensitivity and specificity at the point of maximum accuracy in both H (sensitivity = 89.56%, specificity = 94.54%, AUC = 0.97) and IMR90 (sensitivity = 96.34%, 1−specificity = 97.09%, AUC = 0.99).

In van't Veer et al. [ 13]'s work, 11823860_ST2 gene set was reduced to the famous 70-gene signature by optimizing the number of genes for maximum accuracy in leave-one-out cross validation [ 13].

The evolving accuracy of the RCE-SVM classifier using features from behavioral data, resting state BOLD intensities and task activations is shown in the top panel of Fig. 2. Table 2 shows the corresponding maximum accuracies achieved and the ranking of the features for maximum accuracy based on their SVM scores.

Table 8 summarises the available literature on machine learning algorithms for binary (I123 FP-CIT classI123 FP-CITi.e. normal vs abnormal image appearanclassification0, listed in order of reported maximum accuracy figures, where available.e

Therefore in this proposed work the main focus is to design the algorithm based on level set segmentation, wavelets filters and artificial neural network (ANN) architecture for detection of Cholesterol in real time using biomedical images with the help of MATLAB with maximum accuracy of 98.8%.

Another study [25] reported using nonlinear parameters such as ApEn, sample entropy, Lyapunov exponent, and higher-order spectra for feature extraction and detection of alcoholics with maximum accuracy of 91.7% with support vector machine (SVM) classifier.

These schemes showed high performances with both training and test sets and many combinations of features (with a maximum accuracy of 96.67%).