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1 | | -# Data-Visualizations-and-ML-Algorithms-using-R |
2 | | -Basic data visualizations, Statistics and Machine Learning algorithms are implemented using R Language |
| 1 | + |
| 2 | +# ILLUSTRATED CONCEPTS |
| 3 | +* Following Graphs are explained with small use cases<br> |
| 4 | +<table border="0"> |
| 5 | + <tr> |
| 6 | + <td> 2D Pie Charts </td> |
| 7 | + <td> 3D Pie Charts </td> |
| 8 | + <td> Barplots </td> |
| 9 | + <td> Stacked Barplots </td> |
| 10 | + </tr> |
| 11 | + <tr> |
| 12 | + <td> BoxPlots </td> |
| 13 | + <td> Histograms </td> |
| 14 | + <td> ScatterPlots </td> |
| 15 | + <td> Line Charts </td> |
| 16 | + </tr> |
| 17 | + <tr> |
| 18 | + <td> RasterPlots </td> |
| 19 | + <td> Frequency Polygons </td> |
| 20 | + <td> JitterPlots </td> |
| 21 | + <td> ViolinPlots </td> |
| 22 | + </tr> |
| 23 | +</table> |
| 24 | + |
| 25 | +* Commonly used plots in <b>ggplot2 library</b> are explained<br> |
| 26 | + |
| 27 | +* <b>map_data</b> for basic map functions<br> |
| 28 | + |
| 29 | +* <b>Leaflet library</b> for advanced interactive map functions<br> |
| 30 | + |
| 31 | +* Performing data visualization on <b>Excel Data</b> using <b>readxl library</b><br> |
| 32 | + -Use <b>"Train.xlsx"</b> as sample Excel file<br> |
| 33 | + |
| 34 | +* Following <b>Statistical operations</b> have been performed<br> |
| 35 | +<table border="0"> |
| 36 | + <tr> |
| 37 | + <td> Mean </td> |
| 38 | + <td> Normal distribution - PDF </td> |
| 39 | + <td> Binomial distribution - PDF </td> |
| 40 | + <td> Analysis of Variance </td> |
| 41 | + </tr> |
| 42 | + <tr> |
| 43 | + <td> Median </td> |
| 44 | + <td> Normal distribution - CDF </td> |
| 45 | + <td> Binomial distribution - CDF </td> |
| 46 | + <td> Time Series </td> |
| 47 | + </tr> |
| 48 | + <tr> |
| 49 | + <td> Mode </td> |
| 50 | + <td> Normal distribution - Quantile </td> |
| 51 | + <td> Binomial distribution - Quantile </td> |
| 52 | + </tr> |
| 53 | +</table> |
| 54 | + |
| 55 | +* Following <b>Machine Learning Algorithms</b> have been explained<br> |
| 56 | +<table border="0"> |
| 57 | + <tr> |
| 58 | + <td> Linear Regression </td> |
| 59 | + <td> Decision Trees </td> |
| 60 | + <td> Hierarchial Clustering </td> |
| 61 | + </tr> |
| 62 | + <tr> |
| 63 | + <td> Multiple Linear Regression </td> |
| 64 | + <td> Random Forest </td> |
| 65 | + <td> K-means Clustering </td> |
| 66 | + </tr> |
| 67 | + <tr> |
| 68 | + <td> Logistic Regression </td> |
| 69 | + <td> Survival Analysis </td> |
| 70 | + </tr> |
| 71 | +</table> |
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