Man pages for MarcoNiemann/kaggle_house
Analysing House Prices in Ames, Iowa and Build a Sales Price Prediction Model
| analysis.dotplot | Generate Outlier Point Plot |
| analysis.dotplot.all | Generate Outlier Point Plots |
| api.submit | Submit Results to Kaggle |
| cpp_bind | Combine two 'NumericVector's into a 'NumericMatrix' |
| cpp_regex_selector_name | Extract Selector Name From Variable Name |
| cpp_rep_na_chr | Remove 'NA' from 'CharacterVector' |
| cpp_rep_na_num | Remove 'NA' from 'NumericVector' |
| cpp_valueOccurrencesToPoints | Convert Value Occurences to Points |
| create_barplot | Create Bar Plot |
| data.generate_data_views | Data view generation function |
| echo | Set Cat Function to Echo variable |
| echoln | Write String to Output with appended Newline |
| feature.boruta | Boruta Feature Selection - Wrapper |
| feature.boruta.checkInputParams | Check Boruta Feature Selection Input Parameters |
| feature.boruta.comp | Boruta Feature Selection |
| feature.boruta.fixNA | Remove 'NA' Containing Observations |
| feature.boruta.formula | Create Formula Based on Boruta Selected Features |
| feature.boruta.report | Create PDF and Text Reports About Selected Boruta Features |
| feature.boruta.selected | Provide all Non-Rejected Boruta Features |
| feature.boruta.tentative | Check For Tentative Variables |
| feature.boruta.variables | Obtain List of Confirmed, Tentative and Rejected Variables |
| feature.lasso | Lasso feature selection |
| general_barplot | Generate Bar Plots for Dataset Analysis |
| general_hist | Create Histogram of Numeric Data (to visualize Distribution) |
| general_plot | Create Scatterplot of Data (to visualize Correlations) |
| general_qq | Create a QQ-Plot of Numeric Data (to Analyse the Normality... |
| imputation.test | Impute tst data |
| imputation.train | Impute training data |
| KaggleHouse | Kaggle House Analytial Package |
| learner.deeplearning | Deep Learning with h2o tuned by mlr |
| learner.lasso | Basic glmnet learner |
| learner.stacked | Stacked learner |
| learner.xgboost | Basic xgboost learner |
| plot_against_var | 2D plot generator |
| prepare.transform_data | Data transformation function |
| preprocess.generate_cleaned_data | Cleaning data function |
| rda.conversion.checkRawData | Get List of RAW data files. |
| rda.conversion.convertData | Convert RAW data to RDA data. |
| rda.conversion.ensureDataDir | Ensure Existance of Data Directory |
| rda.conversion.loadDataFile | Load data from RAW data file |
| rda.conversion.saveAsRDA | Convert Loaded Data to RDA File. |
| run_descriptive | Descriptive analysis |
| run_generate_data | Function for generating datasets |
| run_learner | Main stacked learner |
| util.contain_na | Check Data Columns for 'NA' Values |
| util.ensure.dir | Ensure Existance of Directory |
| util.generate.submit | Generate a Kaggle-submitable CSV from the Predicted Data |
| util.list_to_df | Convert List of Matrices to 'data.frame' |
| util.list_to_matrix | Convert list of matrices to matrix |
| util.mse | Compute the MSE between two 'data.frame's |
| util.na.rm | Clear Matrix of all 'NA' rows. |
| util.number_na | Count Number of 'NA' Values in a 'data.frame' |
| util.panel.cor | Define a Scatterplot Panel to Show Correlation Coefficients |
| util.remove.fileextension | Remove File-Extension from Filepath |
| util.write_csv | Write data to a CSV-file. |
