Assessment of model performance on sparse datasets with different degrees of sparsity (1–8 of 9 features) and sparsity distributions (Real-world, Random, Terminal, Central). Colored lines denote mean root mean squared error; shaded bands represent 99% confidence intervals. (TIF)</p
<p>Each panel represents a different combination of randomization algorithm, metric and criterion fo...
Thesis (Ph.D.)--University of Washington, 2019The concept of `sparsity' is common to see in many top...
<p>Histograms show distribution frequencies and curves of best fit for: A) Correct item identificati...
Assessment of model performance on sparse datasets with different degrees of sparsity (1–10 of 11 fe...
Models assessed on sparse datasets with sample size sequentially increasing twofold. Amount of spars...
All tested sparsity distributions applied to sample dataset of 500 audiograms. Quantity of sparsity ...
Model performance assessment given different sparsity distributions. Quantity of missing data varied...
A Empirical cumulative density function for the stimulus-based condition RTs, plotted separately for...
<p>A) Degree distributions, both in-degree (blue) and out-degree (red), for the coupling matrices es...
<p>The mean detection rate of the six sparse features on different <i>k</i> and <i>ε</i>.</p
Performance data (RMSE/variance explained) for each of the three models in the paper; PLS, PCR, and ...
Constructing the reference modes is a critical step in system dynamics modeling. Estimat-ing rates f...
To obtain the curve for one layer, a total of 16 values were chosen non-uniformly between 0.001 and ...
<p>a) Performance on absolute (red) and relative (black) abundances as a function of sample size for...
The red line represents the coefficient from the observed network properties. The observed value is ...
<p>Each panel represents a different combination of randomization algorithm, metric and criterion fo...
Thesis (Ph.D.)--University of Washington, 2019The concept of `sparsity' is common to see in many top...
<p>Histograms show distribution frequencies and curves of best fit for: A) Correct item identificati...
Assessment of model performance on sparse datasets with different degrees of sparsity (1–10 of 11 fe...
Models assessed on sparse datasets with sample size sequentially increasing twofold. Amount of spars...
All tested sparsity distributions applied to sample dataset of 500 audiograms. Quantity of sparsity ...
Model performance assessment given different sparsity distributions. Quantity of missing data varied...
A Empirical cumulative density function for the stimulus-based condition RTs, plotted separately for...
<p>A) Degree distributions, both in-degree (blue) and out-degree (red), for the coupling matrices es...
<p>The mean detection rate of the six sparse features on different <i>k</i> and <i>ε</i>.</p
Performance data (RMSE/variance explained) for each of the three models in the paper; PLS, PCR, and ...
Constructing the reference modes is a critical step in system dynamics modeling. Estimat-ing rates f...
To obtain the curve for one layer, a total of 16 values were chosen non-uniformly between 0.001 and ...
<p>a) Performance on absolute (red) and relative (black) abundances as a function of sample size for...
The red line represents the coefficient from the observed network properties. The observed value is ...
<p>Each panel represents a different combination of randomization algorithm, metric and criterion fo...
Thesis (Ph.D.)--University of Washington, 2019The concept of `sparsity' is common to see in many top...
<p>Histograms show distribution frequencies and curves of best fit for: A) Correct item identificati...