diff --git a/cesium_app/handlers/model.py b/cesium_app/handlers/model.py
index a43e5f2..d2fa973 100644
--- a/cesium_app/handlers/model.py
+++ b/cesium_app/handlers/model.py
@@ -67,11 +67,24 @@ def _build_model_compute_statistics(fset_path, model_type, model_params,
model = GridSearchCV(model, params_to_optimize,
n_jobs=n_jobs)
model.fit(fset, data['labels'])
- score = model.score(fset, data['labels'])
+
+ metrics = {}
+ metrics['train_score'] = model.score(fset, data['labels'])
+
best_params = model.best_params_ if params_to_optimize else {}
joblib.dump(model, model_path)
- return score, best_params
+ if model_type == 'RandomForestClassifier':
+ if params_to_optimize:
+ model = model.best_estimator_
+ if hasattr(model, 'oob_score_'):
+ metrics['oob_score'] = model.oob_score_
+ if hasattr(model, 'feature_importances_'):
+ metrics['feature_importances'] = dict(zip(
+ fset.columns.get_level_values(0).tolist(),
+ model.feature_importances_.tolist()))
+
+ return metrics, best_params
class ModelHandler(BaseHandler):
@@ -102,12 +115,12 @@ def get(self, model_id=None, action=None):
@auth_or_token
async def _await_model_statistics(self, model_stats_future, model):
try:
- score, best_params = await model_stats_future
+ model_metrics, best_params = await model_stats_future
model = DBSession().merge(model)
model.task_id = None
model.finished = datetime.datetime.now()
- model.train_score = score
+ model.metrics = model_metrics
model.params.update(best_params)
DBSession().commit()
diff --git a/cesium_app/models.py b/cesium_app/models.py
index adf357a..dadcb1e 100644
--- a/cesium_app/models.py
+++ b/cesium_app/models.py
@@ -90,7 +90,7 @@ class Model(Base):
file_uri = sa.Column(sa.String(), nullable=True, index=True)
task_id = sa.Column(sa.String())
finished = sa.Column(sa.DateTime)
- train_score = sa.Column(sa.Float)
+ metrics = sa.Column(sa.JSON, nullable=True)
featureset = relationship('Featureset')
project = relationship('Project')
diff --git a/cesium_app/tests/frontend/test_build_model.py b/cesium_app/tests/frontend/test_build_model.py
index af27b64..7fe3f71 100644
--- a/cesium_app/tests/frontend/test_build_model.py
+++ b/cesium_app/tests/frontend/test_build_model.py
@@ -96,16 +96,19 @@ def test_cannot_build_model_unlabeled_data(driver, project, featureset):
"//div[contains(.,'Cannot build model for unlabeled feature set.')]")
-def test_model_info_display(driver, project, featureset, model):
+@pytest.mark.parametrize('featureset__name, model_type',
+ [('class', 'RandomForestClassifier (fast)')])
+def test_model_info_display(driver, project, featureset, model_type):
driver.refresh()
- proj_select = Select(driver.find_element_by_css_selector('[name=project]'))
- proj_select.select_by_value(str(project.id))
- driver.find_element_by_id('react-tabs-6').click()
+ _build_model(project.id, model_type, driver)
- driver.wait_for_xpath("//td[contains(text(),'{}')]".format(model.name)).click()
+ driver.wait_for_xpath("//td[contains(text(), 'Completed')]").click()
+ time.sleep(0.5)
assert driver.wait_for_xpath("//th[contains(text(),'Model Type')]")\
.is_displayed()
- assert driver.wait_for_xpath("//th[contains(text(),'Hyper"
- "parameters')]").is_displayed()
- assert driver.wait_for_xpath("//th[contains(text(),'Training "
- "Data Score')]").is_displayed()
+ assert driver.wait_for_xpath("//th[contains(text(),"
+ "'Hyperparameters')]").is_displayed()
+ assert driver.wait_for_xpath("//th[contains(text(),"
+ "'train_score')]").is_displayed()
+ assert driver.wait_for_xpath("//canvas[@class='chartjs-render-monitor']")\
+ .is_displayed()
diff --git a/package.json b/package.json
index 331ba17..76c7eba 100644
--- a/package.json
+++ b/package.json
@@ -9,12 +9,14 @@
"bokehjs": "^0.12.5",
"bootstrap": "^3.3.7",
"bootstrap-css": "^3.0.0",
+ "chart.js": "^2.7.1",
"css-loader": "^0.26.2",
"exports-loader": "^0.6.4",
"imports-loader": "^0.7.1",
"jquery": "^3.1.1",
"prop-types": "^15.5.10",
"react": "^15.1.0",
+ "react-chartjs-2": "^2.7.0",
"react-dom": "^15.1.0",
"react-redux": "^5.0.3",
"react-tabs": "^0.8.2",
diff --git a/static/js/components/FeatureImportances.jsx b/static/js/components/FeatureImportances.jsx
new file mode 100644
index 0000000..10d3431
--- /dev/null
+++ b/static/js/components/FeatureImportances.jsx
@@ -0,0 +1,42 @@
+import React from 'react';
+import PropTypes from 'prop-types';
+import { HorizontalBar } from 'react-chartjs-2';
+
+
+const FeatureImportancesBarchart = props => {
+ const sorted_features = Object.keys(props.data).sort(
+ (a, b) => props.data[b] - props.data[a]
+ ).slice(0, 15);
+ const values = sorted_features.map(feature => props.data[feature]);
+ const data = {
+ labels: sorted_features,
+ datasets: [
+ {
+ label: 'Feature Importance',
+ backgroundColor: '#2222ff',
+ hoverBackgroundColor: '#5555ff',
+ data: values
+ }
+ ]
+ };
+ const options = {
+ scales: {
+ xAxes: [{
+ ticks: {
+ min: 0.0
+ }
+ }]
+ }
+ };
+
+ return (
+
+
+
+ );
+};
+FeatureImportancesBarchart.propTypes = {
+ data: PropTypes.array.isRequired
+};
+
+export default FeatureImportancesBarchart;
diff --git a/static/js/components/Models.jsx b/static/js/components/Models.jsx
index 8f3b6aa..38d16be 100644
--- a/static/js/components/Models.jsx
+++ b/static/js/components/Models.jsx
@@ -13,6 +13,7 @@ import Delete from './Delete';
import Download from './Download';
import { $try, reformatDatetime } from '../utils';
import FoldableRow from './FoldableRow';
+import FeatureImportances from './FeatureImportances';
const ModelsTab = props => (
@@ -178,7 +179,8 @@ const ModelInfo = props => (
| Model Type |
Hyperparameters |
- Training Data Score |
+ {Object.keys(props.model.metrics).map(metric =>
+ {metric} | )}
@@ -200,9 +202,16 @@ const ModelInfo = props => (
-
- {props.model.train_score}
- |
+ {
+ Object.keys(props.model.metrics).map(metric => (
+
+ {
+ metric == 'feature_importances' ?
+ :
+ props.model.metrics[metric].toFixed(3)
+ }
+ | ))
+ }