mu = 12.02 and sigma = 0.40

              Total   Percent
PoolQC         2908  0.996915
MiscFeature    2812  0.964004
Alley          2719  0.932122
Fence          2346  0.804251
FireplaceQu    1420  0.486802
LotFrontage     486  0.166610
GarageCond      159  0.054508
GarageQual      159  0.054508
GarageYrBlt     159  0.054508
GarageFinish    159  0.054508
GarageType      157  0.053822
BsmtCond         82  0.028111
BsmtExposure     82  0.028111
BsmtQual         81  0.027768
BsmtFinType2     80  0.027425
BsmtFinType1     79  0.027083
MasVnrType       24  0.008228
MasVnrArea       23  0.007885
MSZoning          4  0.001371
BsmtHalfBath      2  0.000686
Functional        2  0.000686
BsmtFullBath      2  0.000686
BsmtFinSF2        1  0.000343
BsmtUnfSF         1  0.000343
BsmtFinSF1        1  0.000343
Exterior2nd       1  0.000343
TotalBsmtSF       1  0.000343
Exterior1st       1  0.000343
SaleType          1  0.000343
Electrical        1  0.000343
KitchenQual       1  0.000343
GarageCars        1  0.000343
GarageArea        1  0.000343
ElasticNetCV(alphas=[0.0001, 0.0005, 0.001, 0.01, 0.1, 1, 10], copy_X=True,
       cv=None, eps=0.001, fit_intercept=True,
       l1_ratio=[0.01, 0.1, 0.5, 0.9, 0.99], max_iter=5000, n_alphas=100,
       n_jobs=1, normalize=False, positive=False, precompute='auto',
       random_state=None, selection='cyclic', tol=0.0001, verbose=0)
R2: 0.9375476904713028
RMSE: 0.09510356919204585
RMSLE: 0.007404587030567225
Test
R2: 0.9241970969211174
RMSE: 0.10801284037386255
RMSLE: 0.008503460503189928
Accuracy: 0.92 (+/- 0.02)
GradientBoostingRegressor(alpha=0.9, criterion='friedman_mse', init=None,
             learning_rate=0.05, loss='huber', max_depth=3,
             max_features='sqrt', max_leaf_nodes=None,
             min_impurity_decrease=0.0, min_impurity_split=None,
             min_samples_leaf=15, min_samples_split=10,
             min_weight_fraction_leaf=0.0, n_estimators=3000,
             presort='auto', random_state=None, subsample=1.0, verbose=0,
             warm_start=False)
R2: 0.9712365659486509
RMSE: 0.06489702799840345
RMSLE: 0.005148721510078062
Test
R2: 0.8856412136806209
RMSE: 0.12677478597418662
RMSLE: 0.010065803355386425
Accuracy: 0.91 (+/- 0.03)
XGBRegressor(base_score=0.5, colsample_bylevel=1, colsample_bytree=1, gamma=0,
       learning_rate=0.05, max_delta_step=0, max_depth=3,
       min_child_weight=1, missing=None, n_estimators=3000, nthread=-1,
       objective='reg:linear', reg_alpha=0, reg_lambda=1,
       scale_pos_weight=1, seed=0, silent=True, subsample=1)
R2: 0.998102033663671
RMSE: 0.01716734991141679
RMSLE: 0.0013246240985368375
Test
R2: 0.8912268252304474
RMSE: 0.12701108893000432
RMSLE: 0.010024565631835718
Accuracy: 0.91 (+/- 0.04)