A) A typical distribution of states in a sample training set (N = 9009). B) A visualization of the performance of the ML algorithm on sample simulated data (N = 1001).</p
<p>(<b>a</b>) The nodes, leaves and total accuracy of states reconstruction for simulations with var...
<p>The class distribution of the numbers of training, validation and testing samples.</p
For each of the 80 trials evidencetotal was calculated based on the stimulus parameters and the weig...
The figure shows the state distribution of the accelerations, where the state number is designed as ...
A count matrix undergoes pre-processing, including normalization and filtering. The data is randomly...
(A) Histogram of the mutual information rates of the states, Ri. (B) Histogram of the logarithm of s...
The process of FS and classification consists of the following steps: 1) create 100 random splits of...
Number of classes and distributions used to simulate the systematic effects for the large (D1) and s...
<p>Probability density functions (top) for evidence that stimuli come from class A or B (e.g., old o...
Distribution of original and down-sampled train and test samples across each target class (a) Traini...
<p>Ordered distributions of accuracies of trained models grouped by learning technique (combined hig...
Abstract. We propose a novel approach for the estimation of the size of training sets that are neede...
(a) Steady state distribution based on non-bonded configuration simulations; (b) Steady state distri...
<p>This table summarizes the performances estimates of the two machine-learning methods used in the ...
<p>(A) Training set marker states. The eight possible marker states for the three indicated markers ...
<p>(<b>a</b>) The nodes, leaves and total accuracy of states reconstruction for simulations with var...
<p>The class distribution of the numbers of training, validation and testing samples.</p
For each of the 80 trials evidencetotal was calculated based on the stimulus parameters and the weig...
The figure shows the state distribution of the accelerations, where the state number is designed as ...
A count matrix undergoes pre-processing, including normalization and filtering. The data is randomly...
(A) Histogram of the mutual information rates of the states, Ri. (B) Histogram of the logarithm of s...
The process of FS and classification consists of the following steps: 1) create 100 random splits of...
Number of classes and distributions used to simulate the systematic effects for the large (D1) and s...
<p>Probability density functions (top) for evidence that stimuli come from class A or B (e.g., old o...
Distribution of original and down-sampled train and test samples across each target class (a) Traini...
<p>Ordered distributions of accuracies of trained models grouped by learning technique (combined hig...
Abstract. We propose a novel approach for the estimation of the size of training sets that are neede...
(a) Steady state distribution based on non-bonded configuration simulations; (b) Steady state distri...
<p>This table summarizes the performances estimates of the two machine-learning methods used in the ...
<p>(A) Training set marker states. The eight possible marker states for the three indicated markers ...
<p>(<b>a</b>) The nodes, leaves and total accuracy of states reconstruction for simulations with var...
<p>The class distribution of the numbers of training, validation and testing samples.</p
For each of the 80 trials evidencetotal was calculated based on the stimulus parameters and the weig...
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