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Stackoverflow #2

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Stackoverflow #2

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https://github.com/Poojavenkata/stackoverflow.git
Poojavenkata Dec 29, 2019
2347130
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Poojavenkata Dec 29, 2019
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5 changes: 3 additions & 2 deletions Salary.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -274,7 +274,8 @@
"%matplotlib inline\n",
"\n",
"df = pd.read_csv('./survey_results_public.csv')\n",
"df.head()"
"df.head()\n",
"df.tail()"
]
},
{
Expand Down Expand Up @@ -5774,7 +5775,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
"version": "3.7.3"
}
},
"nbformat": 4,
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3 changes: 3 additions & 0 deletions Salary_ML.py
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Expand Up @@ -44,6 +44,7 @@ def clean_data(df):
X = df
return X, y


def find_optimal_lm_mod(X, y, cutoffs, test_size = .30, random_state=42, plot=True):
'''
INPUT
Expand All @@ -54,6 +55,7 @@ def find_optimal_lm_mod(X, y, cutoffs, test_size = .30, random_state=42, plot=Tr
random_state - int, default 42, controls random state for train_test_split
plot - boolean, default 0.3, True to plot result


OUTPUT
r2_scores_test - list of floats of r2 scores on the test data
r2_scores_train - list of floats of r2 scores on the train data
Expand Down Expand Up @@ -110,6 +112,7 @@ def main():
X, y = clean_data(df)
#cutoffs here pertains to the number of missing values allowed in the used columns.
#Therefore, lower values for the cutoff provides more predictors in the model.
##################################
cutoffs = [5000, 3500, 2500, 1000, 100, 50, 30, 20, 10, 5]

r2_scores_test, r2_scores_train, lm_model, X_train, X_test, y_train, y_test = find_optimal_lm_mod(X, y, cutoffs, plot=False)
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