The diagonal cells are those representing correctly classified subjects (number of occurrences in each cells are given as N), and these cells are shaded in blue. Off-diagonal cells represents various events of misclassification. Observed/predicted co-occurrences are also accompanied, for each cell, with corresponding information about gender ratio (F/M), confirmed age at inclusion larger than 65 years (Age1 > 65), and volume means in microliters of left and right lateral ventricle (Vol1L and Vol1R), respectively, at time of subject inclusion in the study.</p
<p>Response variables were selected and a linear discriminant classifier was trained using the trans...
Classifications of the validation data (columns) are compared to the ground truth (rows). Numbers ar...
<p>The rows of this matrix indicate the groups of the subjects (ground truth), and the columns indic...
<p>The rows of the matrix indicate the actual roughness provided to the participants and the columns...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
<p>The upper number in each entry of the matrix is the average number of actual recognised classes i...
(a) Recovery rates across families. Rows represent true models/families (used to simulate data), and...
Features included in the model are: age group, sex, and laboratory blood test results of ten CBC par...
The labels are as follows, NL: healthy, MCI: mild cognitive impairment, AD: Alzheimer’s disease. The...
<p>The matrices show the average locations estimated by the classifier as a function of the actual w...
<p>The matrices show the average locations estimated by the classifier as a function of the actual w...
(1) only each prediction model after data preprocessing, where (a) LR, (c) RF, (e) GB, (g) DNN, (i) ...
<p>Confusion matrix showing the actual and predicted age groups in the task of age estimation by hum...
Multinomial logistic regression results for factors associated with misperception of weight among fe...
(a) Fine; (b) Medium; (c) Coarse; (d) Cosine; (e) Cubic; (f) Weighted; (g) Logistic Regression.</p
<p>Response variables were selected and a linear discriminant classifier was trained using the trans...
Classifications of the validation data (columns) are compared to the ground truth (rows). Numbers ar...
<p>The rows of this matrix indicate the groups of the subjects (ground truth), and the columns indic...
<p>The rows of the matrix indicate the actual roughness provided to the participants and the columns...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
<p>The upper number in each entry of the matrix is the average number of actual recognised classes i...
(a) Recovery rates across families. Rows represent true models/families (used to simulate data), and...
Features included in the model are: age group, sex, and laboratory blood test results of ten CBC par...
The labels are as follows, NL: healthy, MCI: mild cognitive impairment, AD: Alzheimer’s disease. The...
<p>The matrices show the average locations estimated by the classifier as a function of the actual w...
<p>The matrices show the average locations estimated by the classifier as a function of the actual w...
(1) only each prediction model after data preprocessing, where (a) LR, (c) RF, (e) GB, (g) DNN, (i) ...
<p>Confusion matrix showing the actual and predicted age groups in the task of age estimation by hum...
Multinomial logistic regression results for factors associated with misperception of weight among fe...
(a) Fine; (b) Medium; (c) Coarse; (d) Cosine; (e) Cubic; (f) Weighted; (g) Logistic Regression.</p
<p>Response variables were selected and a linear discriminant classifier was trained using the trans...
Classifications of the validation data (columns) are compared to the ground truth (rows). Numbers ar...
<p>The rows of this matrix indicate the groups of the subjects (ground truth), and the columns indic...