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{"duration": 84.61651301383972, "input_args": {"XData": " sepal_l sepal_w petal_l petal_w\n0 6.3 3.3 6.0 2.5\n1 7.1 3.0 5.9 2.1\n2 5.8 2.7 5.1 1.9\n3 6.3 2.9 5.6 1.8\n4 7.6 3.0 6.6 2.1\n.. ... ... ... ...\n145 5.1 3.8 1.6 0.2\n146 5.0 3.5 1.6 0.6\n147 5.1 3.4 1.5 0.2\n148 4.6 3.2 1.4 0.2\n149 4.8 3.0 1.4 0.3\n\n[150 rows x 4 columns]", "yData": "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]", "clf": "LinearDiscriminantAnalysis(n_components=None, priors=None, shrinkage=0.99,\n solver='eigen', store_covariance=False, tol=0.0001)", "params": "{'shrinkage': [0.0, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.11, 0.12, 0.13, 0.14, 0.15, 0.16, 0.17, 0.18, 0.19, 0.2, 0.21, 0.22, 0.23, 0.24, 0.25, 0.26, 0.27, 0.28, 0.29, 0.3, 0.31, 0.32, 0.33, 0.34, 0.35000000000000003, 0.36, 0.37, 0.38, 0.39, 0.4, 0.41000000000000003, 0.42, 0.43, 0.44, 0.45, 0.46, 0.47000000000000003, 0.48, 0.49, 0.5, 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.5700000000000001, 0.58, 0.59, 0.6, 0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67, 0.68, 0.6900000000000001, 0.7000000000000001, 0.71, 0.72, 0.73, 0.74, 0.75, 0.76, 0.77, 0.78, 0.79, 0.8, 0.81, 0.8200000000000001, 0.8300000000000001, 0.84, 0.85, 0.86, 0.87, 0.88, 0.89, 0.9, 0.91, 0.92, 0.93, 0.9400000000000001, 0.9500000000000001, 0.96, 0.97, 0.98, 0.99], 'solver': ['lsqr', 'eigen']}", "eachAlgor": "'LDA'", "AlgorithmsIDsEnd": "1996", "toggle": "1"}} |
||||
@ -0,0 +1 @@ |
||||
{"duration": 484.606406211853, "input_args": {"XData": " Age Sex Cp Trestbps Chol ... Exang Oldpeak Slope Ca Thal\n0 63 1 3 145 233 ... 0 2.3 0 0 1\n1 37 1 2 130 250 ... 0 3.5 0 0 2\n2 41 0 1 130 204 ... 0 1.4 2 0 2\n3 56 1 1 120 236 ... 0 0.8 2 0 2\n4 57 0 0 120 354 ... 1 0.6 2 0 2\n.. ... ... .. ... ... ... ... ... ... .. ...\n298 57 0 0 140 241 ... 1 0.2 1 0 3\n299 45 1 3 110 264 ... 0 1.2 1 0 3\n300 68 1 0 144 193 ... 0 3.4 1 2 3\n301 57 1 0 130 131 ... 1 1.2 1 1 3\n302 57 0 1 130 236 ... 0 0.0 1 1 2\n\n[303 rows x 13 columns]", "yData": "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]", "clf": "MLPClassifier(activation='tanh', alpha=0.00081, batch_size='auto', beta_1=0.9,\n beta_2=0.999, early_stopping=False, epsilon=1e-08,\n hidden_layer_sizes=(100,), learning_rate='constant',\n learning_rate_init=0.001, max_fun=15000, max_iter=100,\n momentum=0.9, n_iter_no_change=10, nesterovs_momentum=True,\n power_t=0.5, random_state=42, shuffle=True, solver='sgd',\n tol=0.00081, validation_fraction=0.1, verbose=False,\n warm_start=False)", "params": "{'alpha': [1e-05, 0.00021, 0.00041000000000000005, 0.0006100000000000001, 0.0008100000000000001], 'tol': [1e-05, 0.00041000000000000005, 0.0008100000000000001], 'max_iter': [100], 'activation': ['relu', 'identity', 'logistic', 'tanh'], 'solver': ['adam', 'sgd']}", "eachAlgor": "'MLP'", "AlgorithmsIDsEnd": "1236", "toggle": "1"}} |
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{"duration": 585.050076007843, "input_args": {"XData": " sepal_l sepal_w petal_l petal_w\n0 6.3 3.3 6.0 2.5\n1 7.1 3.0 5.9 2.1\n2 5.8 2.7 5.1 1.9\n3 6.3 2.9 5.6 1.8\n4 7.6 3.0 6.6 2.1\n.. ... ... ... ...\n145 5.1 3.8 1.6 0.2\n146 5.0 3.5 1.6 0.6\n147 5.1 3.4 1.5 0.2\n148 4.6 3.2 1.4 0.2\n149 4.8 3.0 1.4 0.3\n\n[150 rows x 4 columns]", "yData": "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]", "clf": "SVC(C=4.39, break_ties=False, cache_size=200, class_weight=None, coef0=0.0,\n decision_function_shape='ovr', degree=3, gamma='scale', kernel='sigmoid',\n max_iter=-1, probability=True, random_state=42, shrinking=True, tol=0.001,\n verbose=False)", "params": "{'C': [0.1, 0.21000000000000002, 0.32000000000000006, 0.43000000000000005, 0.54, 0.65, 0.7600000000000001, 0.8700000000000001, 0.9800000000000001, 1.09, 1.2000000000000002, 1.3100000000000003, 1.4200000000000004, 1.5300000000000002, 1.6400000000000003, 1.7500000000000002, 1.8600000000000003, 1.9700000000000004, 2.08, 2.1900000000000004, 2.3000000000000003, 2.4100000000000006, 2.5200000000000005, 2.6300000000000003, 2.7400000000000007, 2.8500000000000005, 2.9600000000000004, 3.0700000000000003, 3.1800000000000006, 3.2900000000000005, 3.4000000000000004, 3.5100000000000007, 3.6200000000000006, 3.7300000000000004, 3.8400000000000007, 3.9500000000000006, 4.0600000000000005, 4.17, 4.28, 4.390000000000001], 'kernel': ['rbf', 'linear', 'poly', 'sigmoid']}", "eachAlgor": "'SVC'", "AlgorithmsIDsEnd": "576", "toggle": "1"}} |
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{"duration": 667.0271377563477, "input_args": {"XData": " sepal_l sepal_w petal_l petal_w\n0 6.3 3.3 6.0 2.5\n1 7.1 3.0 5.9 2.1\n2 5.8 2.7 5.1 1.9\n3 6.3 2.9 5.6 1.8\n4 7.6 3.0 6.6 2.1\n.. ... ... ... ...\n145 5.1 3.8 1.6 0.2\n146 5.0 3.5 1.6 0.6\n147 5.1 3.4 1.5 0.2\n148 4.6 3.2 1.4 0.2\n149 4.8 3.0 1.4 0.3\n\n[150 rows x 4 columns]", "yData": "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]", "clf": "ExtraTreesClassifier(bootstrap=False, ccp_alpha=0.0, class_weight=None,\n criterion='entropy', max_depth=None, max_features='auto',\n max_leaf_nodes=None, max_samples=None,\n min_impurity_decrease=0.0, min_impurity_split=None,\n min_samples_leaf=1, min_samples_split=2,\n min_weight_fraction_leaf=0.0, n_estimators=139,\n n_jobs=None, oob_score=False, random_state=42, verbose=0,\n warm_start=False)", "params": "{'n_estimators': [60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139], 'criterion': ['gini', 'entropy']}", "eachAlgor": "'ExtraT'", "AlgorithmsIDsEnd": "2606", "toggle": "1"}} |
||||
@ -0,0 +1 @@ |
||||
{"duration": 1548.160016298294, "input_args": {"XData": " Age Sex Cp Trestbps Chol ... Exang Oldpeak Slope Ca Thal\n0 63 1 3 145 233 ... 0 2.3 0 0 1\n1 37 1 2 130 250 ... 0 3.5 0 0 2\n2 41 0 1 130 204 ... 0 1.4 2 0 2\n3 56 1 1 120 236 ... 0 0.8 2 0 2\n4 57 0 0 120 354 ... 1 0.6 2 0 2\n.. ... ... .. ... ... ... ... ... ... .. ...\n298 57 0 0 140 241 ... 1 0.2 1 0 3\n299 45 1 3 110 264 ... 0 1.2 1 0 3\n300 68 1 0 144 193 ... 0 3.4 1 2 3\n301 57 1 0 130 131 ... 1 1.2 1 1 3\n302 57 0 1 130 236 ... 0 0.0 1 1 2\n\n[303 rows x 13 columns]", "yData": "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]", "clf": "ExtraTreesClassifier(bootstrap=False, ccp_alpha=0.0, class_weight=None,\n criterion='entropy', max_depth=None, max_features='auto',\n max_leaf_nodes=None, max_samples=None,\n min_impurity_decrease=0.0, min_impurity_split=None,\n min_samples_leaf=1, min_samples_split=2,\n min_weight_fraction_leaf=0.0, n_estimators=139,\n n_jobs=None, oob_score=False, random_state=42, verbose=0,\n warm_start=False)", "params": "{'n_estimators': [60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139], 'criterion': ['gini', 'entropy']}", "eachAlgor": "'ExtraT'", "AlgorithmsIDsEnd": "2606", "toggle": "1"}} |
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||||
<template> |
||||
<button style="float: right;" |
||||
id="addStack" |
||||
v-on:click="valueActiveStFun"> |
||||
<font-awesome-icon icon="save" /> |
||||
{{ valueActiveSt }} |
||||
</button> |
||||
</template> |
||||
|
||||
<script> |
||||
|
||||
import { EventBus } from '../main.js' |
||||
|
||||
export default { |
||||
name: 'saveStack', |
||||
data () { |
||||
return { |
||||
valueActiveSt: 'Store in a new Stack' |
||||
} |
||||
}, |
||||
methods: { |
||||
valueActiveStFun () { |
||||
EventBus.$emit('storeStack') |
||||
} |
||||
} |
||||
} |
||||
</script> |
||||
Loading…
Reference in new issue