T.T. Wong. Parametric methods for comparing the performance of two classification algorithms evaluated by k-fold cross validation on multiple data sets. Pattern Recogn. 65, pp. 97-107, 2017.T. T. Wong. (2017). Parametric methods for comparing the performance of two classification algorithms ...
Table 1. Available options for the “what” parameter when using the set function for adjusting the look of a dendrogram Fig. 2. A tanglegram for comparing two clustering algorithms used on 15 flowers from the Iris dataset. Similar sub-trees are connected by line...
in 201715, which is mainly used for point cloud segmentation and classification. This study used the segmentation module of PointNet++ to segment the femoral head, femoral neck, and femoral shaft. We divided the point cloud datasets into two parts: 50 femur data segmented manually by doctor ...
Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms是俄勒冈州立大学(Oregon State University)CS专业的Thomas G. Dietterich于1998年在Neural Computation上发表的。 该文章以一个问题为引子(Given two learning algorithms A and B and a small data set S, which algorithm will ...
2021), regression trees, and classification algorithms (Cabral et al. 2018), along with K-nearest neighbor, support vector machines, K-means clustering, self-organizing maps, autoencoders, hidden Markov models, and hard competitive learning (Arnold et al. 2014). A prominent gap exists in long...
(NIRS) and machine learning algorithms to improve the non-destructive maturity classification of durian fruit. In a study, two NIRS spectrometers were used to scan durian fruit at different maturity stages, and three supervised machine learning algorithms were tested. The results showed that the use...
In this section, let’s compare the performance of two machine learning algorithms on a binary classification task, then check if the observed difference is statistically significant or not. First, we can use the make_classification() function to create a synthetic dataset with 1,000 samples and...
The agreement coefficient κ between the two classification procedures is about 0.83 when all four self-reported ethnicities are analyzed jointly. However, the agreement between these two methods is almost perfect (κ = 0.98) when the self-reported Hispanics were not considered in the analysis. The...
classification models for cervids can be categorized by whether they were trained with captive [11] or wild animals [7], whether they use low- [9] or high-resolution [8] acceleration data and whether they are binary [18] or multiclass [2] models. A binary model classifies only two ...
This is helpful to find the relations between algorithms and to verify result so it helps to validate our data and result before we conclude any result. It is going to help us to decide that which classification technique we are going to use for forming a decision tree. It has two key ...