Sentence examples for dimension dataset from inspiring English sources
The analysis of a high dimension dataset is primarily based on comparison of variables or observations, using a variety of similarity measures.
The results of the parallel analysis indicate the PAB-S has one dimension (Dataset explained variance = 58.3 % for factor 1 and 4.9 % for factor 2; Parallel Analysis explained variance = 12.6 % for factor 1 and 5.1 % for factor 2). Hence, the scale was submitted to a single-factor ESEM presented in Table 1.
The high dimension dataset can be represented by the following real-valued expression matrix (1 where individuals are scattered on K classes (C_1,ldots,C_K), (n_k) denotes the size of a kth class, for (k= 1,ldots, K) and (n=n_1+cdots +n_K) is the global sample size.
The PCA technique can effectively characterize the internal structure of high dimension dataset by preserving the variance in the data while transforming the data into low dimension space.
Axis information - including any associated transforms - can now be read from images (and higher dimension datasets) which contain axes with 1D transforms on them.
To handle high dimension datasets in the prediction framework, we propose to proceed in five steps.
The volume, one of the famous five Vs that characterize Big Data, is the main challenge that interests the statistician when analyzing high dimension datasets.
In this publication, we introduce new computational tools to analyze gene patterning for three spatial dimension datasets, applied to early Drosophila embryos.
Compared to MinMax, the decrease in the overlap factor was up to 22.4% for the 128 dimensions datasets requiring only 3.8% of the distance calculations performed by it.
We can reduce n dimensions of dataset into k dimensions (where k < n).
