Hugging Face's logo

adrian-lam
/
ubcv-grade-predictor-ridge

Tabular Regression
Scikit-learn
Joblib
skops
Model card Files Community
ubcv-grade-predictor-ridge / README.md
adrian-lam's picture
adrian-lam
Initial commit
7ecf383 verified
preview code
|
raw
history blame contribute delete
50.2 kB
metadata
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
      Course_Min_Last_3y:
        - 71.898305085
      Course_Std_Last_3y:
        - 7.270712022509893
      Prev_50-54:
        - 1
      Prev_55-59:
        - 5
      Prev_60-63:
        - 11
      Prev_64-67:
        - 12
      Prev_68-71:
        - 14
      Prev_72-75:
        - 15
      Prev_76-79:
        - 11
      Prev_80-84:
        - 31
      Prev_85-89:
        - 23
      Prev_90-100:
        - 23
      Prev_<50:
        - 31
      Prev_High:
        - 97
      Prev_Low:
        - 5
      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 <class 'numpy.float64'>
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 <class 'numpy.float64'>
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))])
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.

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]