Sentence examples for binary matching from inspiring English sources

So Mr Srivastava has devised a system called Scout, which compares the old and new versions of the program using a technique known as "binary matching".

Further, we have also illustrated how such a fundamental resemblance can be exploited to obtain other approximate classification performances when binary matching is concerned.

As such, rather than just confining binary matching method to pure Hamming distance calculation, these extensions significantly broaden the practicality of performing binary matching and enable a strong performance resemblance of a powerful classifier such as a multilayer perceptron (MLP) [21] or a SVM [22] when the bits allocation to each dimension is substantially large.

When binary matching is performed, the basic resemblance in (18) can further be exploited to obtain resemblance with the other distance metric-based and machine learning-based classification performance.

According to (11), the total difference in distance of (19) is upper bounded by ∑ d = 1 D 2 ε i 2 d, j 2 d ( max ) d p p. Likewise, to achieve a resembled performance of k-NN classifier [23] and RBF network [24] that use Euclidean distance (L2) as the distance metric, the RHS of (19) can simply be amended and subsequently adopted for binary matching by setting p = 2.

We propose a bias-correction method for models such as binary matched pairs and discuss how the REML estimating equations for mixed linear models can be modified to implement more general models.

But we need to know that binaries match that code and that any tampering can be detected.

For a more in depth analysis of the relationship between the joint data sets sourced from the core scenario survey and the attribute analysis data, the researcher utilized the McNemar Test for Binary Matched Pair.

A simple and frequently used test for binary matched-pairs data is the McNemar test.

We used bootstrapping to estimate 95% CI around mean differences, and McNemar mid-p test for binary matched-pair data (10).

After obtaining the predicted probability values conditional on the observable covariates (the propensity scores) from the binary estimation, matching was done using a matching algorithm that was selected based on the data at hand.