--- library_name: sklearn tags: - sklearn - skops - tabular-regression model_format: pickle model_file: ubcv_grade_predictor_ridge.joblib widget: - structuredData: Campus: - UBCV Course: - 110 CourseLevel: - 1 Course_Avg_Roll_1y: - 73.5864074445 Course_Max_Last_3y: - 91.0 Course_Min_Last_3y: - 71.898305085 Course_Std_Last_3y: - 7.270712022509893 Prev_50-54: - 1.0 Prev_55-59: - 5.0 Prev_60-63: - 11.0 Prev_64-67: - 12.0 Prev_68-71: - 14.0 Prev_72-75: - 15.0 Prev_76-79: - 11.0 Prev_80-84: - 31.0 Prev_85-89: - 23.0 Prev_90-100: - 23.0 Prev_<50: - 31.0 Prev_High: - 97.0 Prev_Low: - 5.0 Prev_Median: - .nan Prev_Percentile (25): - .nan Prev_Percentile (75): - .nan Prof_Courses_Taught: - .nan Prof_Prev_50-54: - .nan Prof_Prev_55-59: - .nan Prof_Prev_60-63: - .nan Prof_Prev_64-67: - .nan Prof_Prev_68-71: - .nan Prof_Prev_72-75: - .nan Prof_Prev_76-79: - .nan Prof_Prev_80-84: - .nan Prof_Prev_85-89: - .nan Prof_Prev_90-100: - .nan Prof_Prev_<50: - .nan Prof_Prev_High: - .nan Prof_Prev_Low: - .nan Prof_Prev_Median: - .nan Prof_Prev_Percentile (25): - .nan Prof_Prev_Percentile (75): - .nan Professor: - '' Session: - W Subject: - CPSC SubjectCourse: - CPSC110 Year: - 2018 Years_Since_Start: - 4 --- # Model description [More Information Needed] ## Intended uses & limitations [More Information Needed] ## Training Procedure [More Information Needed] ### Hyperparameters
Click to expand | Hyperparameter | Value | |----------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------| | memory | | | steps | [('columntransformer', ColumnTransformer(transformers=[('pipeline-1',
Pipeline(steps=[('simpleimputer',
SimpleImputer()),
('standardscaler',
StandardScaler())]),
['Course_Avg_Roll_1y', 'Course_Min_Last_3y',
'Course_Max_Last_3y', 'Course_Std_Last_3y']),
('pipeline-2',
Pipeline(steps=[('simpleimputer',
SimpleImputer(strategy='most_frequent')),
('onehotencoder',
OneHotEncoder(drop='if_b...
SimpleImputer(strategy='most_frequent')),
('ordinalencoder',
OrdinalEncoder(handle_unknown='use_encoded_value',
unknown_value=-1))]),
['CourseLevel', 'Years_Since_Start',
'Prof_Courses_Taught', 'Year']),
('drop', 'drop',
['Reported', 'Section', 'Detail', 'Median',
'Percentile (25)', 'Percentile (75)', 'High',
'Low', '<50', '50-54', '55-59', '60-63',
'64-67', '68-71', '72-75', '76-79', '80-84',
'85-89', '90-100'])])), ('ridge', Ridge(alpha=2.091, random_state=42))] | | transform_input | | | verbose | False | | columntransformer | ColumnTransformer(transformers=[('pipeline-1',
Pipeline(steps=[('simpleimputer',
SimpleImputer()),
('standardscaler',
StandardScaler())]),
['Course_Avg_Roll_1y', 'Course_Min_Last_3y',
'Course_Max_Last_3y', 'Course_Std_Last_3y']),
('pipeline-2',
Pipeline(steps=[('simpleimputer',
SimpleImputer(strategy='most_frequent')),
('onehotencoder',
OneHotEncoder(drop='if_b...
SimpleImputer(strategy='most_frequent')),
('ordinalencoder',
OrdinalEncoder(handle_unknown='use_encoded_value',
unknown_value=-1))]),
['CourseLevel', 'Years_Since_Start',
'Prof_Courses_Taught', 'Year']),
('drop', 'drop',
['Reported', 'Section', 'Detail', 'Median',
'Percentile (25)', 'Percentile (75)', 'High',
'Low', '<50', '50-54', '55-59', '60-63',
'64-67', '68-71', '72-75', '76-79', '80-84',
'85-89', '90-100'])]) | | ridge | Ridge(alpha=2.091, random_state=42) | | columntransformer__force_int_remainder_cols | True | | columntransformer__n_jobs | | | columntransformer__remainder | drop | | columntransformer__sparse_threshold | 0.3 | | columntransformer__transformer_weights | | | columntransformer__transformers | [('pipeline-1', Pipeline(steps=[('simpleimputer', SimpleImputer()),
('standardscaler', StandardScaler())]), ['Course_Avg_Roll_1y', 'Course_Min_Last_3y', 'Course_Max_Last_3y', 'Course_Std_Last_3y']), ('pipeline-2', Pipeline(steps=[('simpleimputer', SimpleImputer(strategy='most_frequent')),
('onehotencoder',
OneHotEncoder(drop='if_binary', handle_unknown='ignore'))]), ['Campus', 'Session', 'SubjectCourse', 'Professor', 'Subject']), ('pipeline-3', Pipeline(steps=[('simpleimputer', SimpleImputer(strategy='most_frequent')),
('ordinalencoder',
OrdinalEncoder(handle_unknown='use_encoded_value',
unknown_value=-1))]), ['CourseLevel', 'Years_Since_Start', 'Prof_Courses_Taught', 'Year']), ('drop', 'drop', ['Reported', 'Section', 'Detail', 'Median', 'Percentile (25)', 'Percentile (75)', 'High', 'Low', '<50', '50-54', '55-59', '60-63', '64-67', '68-71', '72-75', '76-79', '80-84', '85-89', '90-100'])] | | columntransformer__verbose | False | | columntransformer__verbose_feature_names_out | True | | columntransformer__pipeline-1 | Pipeline(steps=[('simpleimputer', SimpleImputer()),
('standardscaler', StandardScaler())]) | | columntransformer__pipeline-2 | Pipeline(steps=[('simpleimputer', SimpleImputer(strategy='most_frequent')),
('onehotencoder',
OneHotEncoder(drop='if_binary', handle_unknown='ignore'))]) | | columntransformer__pipeline-3 | Pipeline(steps=[('simpleimputer', SimpleImputer(strategy='most_frequent')),
('ordinalencoder',
OrdinalEncoder(handle_unknown='use_encoded_value',
unknown_value=-1))]) | | columntransformer__drop | drop | | columntransformer__pipeline-1__memory | | | columntransformer__pipeline-1__steps | [('simpleimputer', SimpleImputer()), ('standardscaler', StandardScaler())] | | columntransformer__pipeline-1__transform_input | | | columntransformer__pipeline-1__verbose | False | | columntransformer__pipeline-1__simpleimputer | SimpleImputer() | | columntransformer__pipeline-1__standardscaler | StandardScaler() | | columntransformer__pipeline-1__simpleimputer__add_indicator | False | | columntransformer__pipeline-1__simpleimputer__copy | True | | columntransformer__pipeline-1__simpleimputer__fill_value | | | columntransformer__pipeline-1__simpleimputer__keep_empty_features | False | | columntransformer__pipeline-1__simpleimputer__missing_values | nan | | columntransformer__pipeline-1__simpleimputer__strategy | mean | | columntransformer__pipeline-1__standardscaler__copy | True | | columntransformer__pipeline-1__standardscaler__with_mean | True | | columntransformer__pipeline-1__standardscaler__with_std | True | | columntransformer__pipeline-2__memory | | | columntransformer__pipeline-2__steps | [('simpleimputer', SimpleImputer(strategy='most_frequent')), ('onehotencoder', OneHotEncoder(drop='if_binary', handle_unknown='ignore'))] | | columntransformer__pipeline-2__transform_input | | | columntransformer__pipeline-2__verbose | False | | columntransformer__pipeline-2__simpleimputer | SimpleImputer(strategy='most_frequent') | | columntransformer__pipeline-2__onehotencoder | OneHotEncoder(drop='if_binary', handle_unknown='ignore') | | columntransformer__pipeline-2__simpleimputer__add_indicator | False | | columntransformer__pipeline-2__simpleimputer__copy | True | | columntransformer__pipeline-2__simpleimputer__fill_value | | | columntransformer__pipeline-2__simpleimputer__keep_empty_features | False | | columntransformer__pipeline-2__simpleimputer__missing_values | nan | | columntransformer__pipeline-2__simpleimputer__strategy | most_frequent | | columntransformer__pipeline-2__onehotencoder__categories | auto | | columntransformer__pipeline-2__onehotencoder__drop | if_binary | | columntransformer__pipeline-2__onehotencoder__dtype | | | columntransformer__pipeline-2__onehotencoder__feature_name_combiner | concat | | columntransformer__pipeline-2__onehotencoder__handle_unknown | ignore | | columntransformer__pipeline-2__onehotencoder__max_categories | | | columntransformer__pipeline-2__onehotencoder__min_frequency | | | columntransformer__pipeline-2__onehotencoder__sparse_output | True | | columntransformer__pipeline-3__memory | | | columntransformer__pipeline-3__steps | [('simpleimputer', SimpleImputer(strategy='most_frequent')), ('ordinalencoder', OrdinalEncoder(handle_unknown='use_encoded_value', unknown_value=-1))] | | columntransformer__pipeline-3__transform_input | | | columntransformer__pipeline-3__verbose | False | | columntransformer__pipeline-3__simpleimputer | SimpleImputer(strategy='most_frequent') | | columntransformer__pipeline-3__ordinalencoder | OrdinalEncoder(handle_unknown='use_encoded_value', unknown_value=-1) | | columntransformer__pipeline-3__simpleimputer__add_indicator | False | | columntransformer__pipeline-3__simpleimputer__copy | True | | columntransformer__pipeline-3__simpleimputer__fill_value | | | columntransformer__pipeline-3__simpleimputer__keep_empty_features | False | | columntransformer__pipeline-3__simpleimputer__missing_values | nan | | columntransformer__pipeline-3__simpleimputer__strategy | most_frequent | | columntransformer__pipeline-3__ordinalencoder__categories | auto | | columntransformer__pipeline-3__ordinalencoder__dtype | | | columntransformer__pipeline-3__ordinalencoder__encoded_missing_value | nan | | columntransformer__pipeline-3__ordinalencoder__handle_unknown | use_encoded_value | | columntransformer__pipeline-3__ordinalencoder__max_categories | | | columntransformer__pipeline-3__ordinalencoder__min_frequency | | | columntransformer__pipeline-3__ordinalencoder__unknown_value | -1 | | ridge__alpha | 2.091 | | ridge__copy_X | True | | ridge__fit_intercept | True | | ridge__max_iter | | | ridge__positive | False | | ridge__random_state | 42 | | ridge__solver | auto | | ridge__tol | 0.0001 |
### Model Plot 
Pipeline(steps=[('columntransformer',ColumnTransformer(transformers=[('pipeline-1',Pipeline(steps=[('simpleimputer',SimpleImputer()),('standardscaler',StandardScaler())]),['Course_Avg_Roll_1y','Course_Min_Last_3y','Course_Max_Last_3y','Course_Std_Last_3y']),('pipeline-2',Pipeline(steps=[('simpleimputer',SimpleImputer(strategy='most_frequent')),('on...OrdinalEncoder(handle_unknown='use_encoded_value',unknown_value=-1))]),['CourseLevel','Years_Since_Start','Prof_Courses_Taught','Year']),('drop', 'drop',['Reported', 'Section','Detail', 'Median','Percentile (25)','Percentile (75)', 'High','Low', '<50', '50-54','55-59', '60-63', '64-67','68-71', '72-75', '76-79','80-84', '85-89','90-100'])])),('ridge', Ridge(alpha=2.091, random_state=42))])
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## Evaluation Results [More Information Needed] # How to Get Started with the Model [More Information Needed] # Model Card Authors This model card is written by following authors: [More Information Needed] # Model Card Contact You can contact the model card authors through following channels: [More Information Needed] # Citation Below you can find information related to citation. **BibTeX:** ``` [More Information Needed] ```