From bf09ffc7187fab70307226c7d3aac6b33e9f4f18 Mon Sep 17 00:00:00 2001 From: Ashish Shukla Date: Tue, 23 Jul 2024 22:55:44 +0530 Subject: [PATCH] model_card_added --- model_card_template.md | 38 +++++++++++++++++++++++++++++++++++++- 1 file changed, 37 insertions(+), 1 deletion(-) diff --git a/model_card_template.md b/model_card_template.md index 0392f3b..72a6da0 100644 --- a/model_card_template.md +++ b/model_card_template.md @@ -3,16 +3,52 @@ For additional information see the Model Card paper: https://arxiv.org/pdf/1810.03993.pdf ## Model Details +Model is created by Ashish Kumar Shukla + +Model use `RandomForestClassifier` from `sklearn.model.RandomForestClassifier` for classification tasks. + +The parameters used are default. ## Intended Use +This model predicts whether a person earns over 50k or not based on the census data. ## Training Data +More details about the training data: https://archive.ics.uci.edu/ml/datasets/census+income + +Extraction was done by Barry Becker from the 1994 Census database. + +Prediction task is to determine whether a person makes over 50K a year. + +Features: + - age: continuous. + - workclass: Private, Self-emp-not-inc, Self-emp-inc, Federal-gov, Local-gov, State-gov, Without-pay, Never-worked. + - fnlwgt: continuous. + - education: Bachelors, Some-college, 11th, HS-grad, Prof-school, Assoc-acdm, Assoc-voc, 9th, 7th-8th, 12th, Masters, 1st-4th, 10th, Doctorate, 5th-6th, Preschool. + - education-num: continuous. + - marital-status: Married-civ-spouse, Divorced, Never-married, Separated, Widowed, Married-spouse-absent, Married-AF-spouse. + - occupation: Tech-support, Craft-repair, Other-service, Sales, Exec-managerial, Prof-specialty, Handlers-cleaners, Machine-op-inspct, Adm-clerical, Farming-fishing, Transport-moving, Priv-house-serv, Protective-serv, Armed-Forces. + - relationship: Wife, Own-child, Husband, Not-in-family, Other-relative, Unmarried. + - race: White, Asian-Pac-Islander, Amer-Indian-Eskimo, Other, Black. + - sex: Female, Male. + - capital-gain: continuous. + - capital-loss: continuous. + - hours-per-week: continuous. + - native-country: United-States, Cambodia, England, Puerto-Rico, Canada, Germany, Outlying-US(Guam-USVI-etc), India, Japan, Greece, South, China, Cuba, Iran, Honduras, Philippines, Italy, Poland, Jamaica, Vietnam, Mexico, Portugal, Ireland, France, Dominican-Republic, Laos, Ecuador, Taiwan, Haiti, Columbia, Hungary, Guatemala, Nicaragua, Scotland, Thailand, Yugoslavia, El-Salvador, Trinadad&Tobago, Peru, Hong, Holand-Netherlands. + +For both training and evaluation, categorical features of the data are encoded using `OneHotEncoder` and the target is transformed using `LabelBinarizer` + ## Evaluation Data +The original dataset is first preprocessed and then split into training and evaluation data with evaluation data size of 20% ## Metrics -_Please include the metrics used and your model's performance on those metrics._ +Performances of the model: +- Precision: 0.71 +- Recall: 0.62 +- Fbeta: 0.67 ## Ethical Considerations +This model is trained on census data. The model is not biased towards any particular group of people. ## Caveats and Recommendations +I recommend that checks are included upstream of any decision-making points to ensure that bias is minimized. \ No newline at end of file