The performance of the proposed model at two extreme thresholds with different sparsity.</p
<p>Performance comparison of the first experiment (results of our proposed algorithm are in bold).</...
<p>Comparison of the performance of our models with that of LACE, assuming a 25% intervention rate.<...
<p>The performances of the different classification algorithms as a function of the number of trials...
<p>The performance comparison of the models trained with different sequence lengths.</p
Comparing performance of the proposed methods built with different number of individual models.</p
Performance of sparse and non-sparse discriminant models in internal validation compared on the same...
<p>Performance comparison of the second experiment (results of our proposed algorithm are in bold).<...
Comparative model performance: Low complexity choices, base rate of comparison: 50%.</p
Performance comparison of CNN models with different region sizes and other baseline models.</p
Assessment of model performance on sparse datasets with different degrees of sparsity (1–10 of 11 fe...
Model performance estimate and generalization gap according to the sample size and the level of task...
Performance comparison of the proposed model and the state-of-the-art methods on DS2.</p
Comparison of performance obtained by our approach with other state-of-the-art algorithms.</p
Performance statistics of the tested algorithms at different activity levels.</p
Comparative model performance: High complexity choices, base rate of comparison: 25%.</p
<p>Performance comparison of the first experiment (results of our proposed algorithm are in bold).</...
<p>Comparison of the performance of our models with that of LACE, assuming a 25% intervention rate.<...
<p>The performances of the different classification algorithms as a function of the number of trials...
<p>The performance comparison of the models trained with different sequence lengths.</p
Comparing performance of the proposed methods built with different number of individual models.</p
Performance of sparse and non-sparse discriminant models in internal validation compared on the same...
<p>Performance comparison of the second experiment (results of our proposed algorithm are in bold).<...
Comparative model performance: Low complexity choices, base rate of comparison: 50%.</p
Performance comparison of CNN models with different region sizes and other baseline models.</p
Assessment of model performance on sparse datasets with different degrees of sparsity (1–10 of 11 fe...
Model performance estimate and generalization gap according to the sample size and the level of task...
Performance comparison of the proposed model and the state-of-the-art methods on DS2.</p
Comparison of performance obtained by our approach with other state-of-the-art algorithms.</p
Performance statistics of the tested algorithms at different activity levels.</p
Comparative model performance: High complexity choices, base rate of comparison: 25%.</p
<p>Performance comparison of the first experiment (results of our proposed algorithm are in bold).</...
<p>Comparison of the performance of our models with that of LACE, assuming a 25% intervention rate.<...
<p>The performances of the different classification algorithms as a function of the number of trials...
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