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result_tables with MinMaxScaler().tex
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\begin{table}
\centering
\caption{}% {'activation': 'logistic', 'alpha': 1e-05, 'hidden_layer_sizes': (5,), 'max_iter': 100, 'random_state': 1, 'solver': 'lbfgs'}}
\begin{tabular}{lrrr}
\toprule
{} & precision & recall & f1-score \\
\midrule
1 & 0,98 & 0,98 & 0,98 \\
2 & 1,00 & 0,91 & 0,95 \\
3 & 0,90 & 1,00 & 0,95 \\
weighted avg & 0,97 & 0,97 & 0,97 \\
\bottomrule
\end{tabular}
\end{table}
\begin{table}
\centering
\caption{}% {'activation': 'tanh', 'alpha': 1e-05, 'hidden_layer_sizes': (5,), 'max_iter': 100, 'random_state': 1, 'solver': 'sgd'}}
\begin{tabular}{lrrr}
\toprule
{} & precision & recall & f1-score \\
\midrule
1 & 0,71 & 1,00 & 0,83 \\
2 & 0,00 & 0,00 & 0,00 \\
3 & 0,00 & 0,00 & 0,00 \\
weighted avg & 0,49 & 0,69 & 0,58 \\
\bottomrule
\end{tabular}
\end{table}
\begin{table}
\centering
\caption{}% {'activation': 'identity', 'alpha': 1e-05, 'hidden_layer_sizes': (20, 10, 5), 'max_iter': 100, 'random_state': 1, 'solver': 'adam'}}
\begin{tabular}{lrrr}
\toprule
{} & precision & recall & f1-score \\
\midrule
1 & 0,74 & 1,00 & 0,85 \\
2 & 1,00 & 0,09 & 0,17 \\
3 & 1,00 & 0,33 & 0,50 \\
weighted avg & 0,82 & 0,75 & 0,69 \\
\bottomrule
\end{tabular}
\end{table}
\begin{table}
\centering
\caption{}% {'activation': 'logistic', 'alpha': 1e-05, 'hidden_layer_sizes': (5,), 'max_iter': 1000, 'random_state': 1, 'solver': 'lbfgs'}}
\begin{tabular}{lrrr}
\toprule
{} & precision & recall & f1-score \\
\midrule
1 & 0,98 & 0,98 & 0,98 \\
2 & 1,00 & 0,91 & 0,95 \\
3 & 0,90 & 1,00 & 0,95 \\
weighted avg & 0,97 & 0,97 & 0,97 \\
\bottomrule
\end{tabular}
\end{table}
\begin{table}
\centering
\caption{}% {'activation': 'identity', 'alpha': 1e-05, 'hidden_layer_sizes': (5, 10, 20), 'max_iter': 1000, 'random_state': 1, 'solver': 'sgd'}}
\begin{tabular}{lrrr}
\toprule
{} & precision & recall & f1-score \\
\midrule
1 & 0,92 & 1,00 & 0,96 \\
2 & 1,00 & 0,73 & 0,84 \\
3 & 1,00 & 0,89 & 0,94 \\
weighted avg & 0,94 & 0,94 & 0,94 \\
\bottomrule
\end{tabular}
\end{table}
\begin{table}
\centering
\caption{}% {'activation': 'identity', 'alpha': 1e-05, 'hidden_layer_sizes': (20, 20), 'max_iter': 1000, 'random_state': 1, 'solver': 'adam'}}
\begin{tabular}{lrrr}
\toprule
{} & precision & recall & f1-score \\
\midrule
1 & 1,00 & 1,00 & 1,00 \\
2 & 1,00 & 1,00 & 1,00 \\
3 & 1,00 & 1,00 & 1,00 \\
weighted avg & 1,00 & 1,00 & 1,00 \\
\bottomrule
\end{tabular}
\end{table}
\begin{table}
\centering
\caption{}% {'activation': 'logistic', 'alpha': 1e-05, 'hidden_layer_sizes': (5,), 'max_iter': 10000, 'random_state': 1, 'solver': 'lbfgs'}}
\begin{tabular}{lrrr}
\toprule
{} & precision & recall & f1-score \\
\midrule
1 & 0,98 & 0,98 & 0,98 \\
2 & 1,00 & 0,91 & 0,95 \\
3 & 0,90 & 1,00 & 0,95 \\
weighted avg & 0,97 & 0,97 & 0,97 \\
\bottomrule
\end{tabular}
\end{table}
\begin{table}
\centering
\caption{}% {'activation': 'tanh', 'alpha': 1e-05, 'hidden_layer_sizes': (5, 10, 20), 'max_iter': 10000, 'random_state': 1, 'solver': 'sgd'}}
\begin{tabular}{lrrr}
\toprule
{} & precision & recall & f1-score \\
\midrule
1 & 0,98 & 0,98 & 0,98 \\
2 & 1,00 & 0,91 & 0,95 \\
3 & 0,90 & 1,00 & 0,95 \\
weighted avg & 0,97 & 0,97 & 0,97 \\
\bottomrule
\end{tabular}
\end{table}
\begin{table}
\centering
\caption{}% {'activation': 'identity', 'alpha': 1e-05, 'hidden_layer_sizes': (20, 20), 'max_iter': 10000, 'random_state': 1, 'solver': 'adam'}}
\begin{tabular}{lrrr}
\toprule
{} & precision & recall & f1-score \\
\midrule
1 & 1,00 & 1,00 & 1,00 \\
2 & 1,00 & 1,00 & 1,00 \\
3 & 1,00 & 1,00 & 1,00 \\
weighted avg & 1,00 & 1,00 & 1,00 \\
\bottomrule
\end{tabular}
\end{table}