prediction
RDZ
10/22/2018
Exploratory Data Analysis and Data Cleaning
- Load the data
training = read.csv("pml-training.csv", na.strings=c("NA","#DIV/0!", ""))
testing = read.csv("pml-testing.csv", na.strings=c("NA","#DIV/0!", ""))head(training)## X user_name raw_timestamp_part_1 raw_timestamp_part_2 cvtd_timestamp
## 1 1 carlitos 1323084231 788290 05/12/2011 11:23
## 2 2 carlitos 1323084231 808298 05/12/2011 11:23
## 3 3 carlitos 1323084231 820366 05/12/2011 11:23
## 4 4 carlitos 1323084232 120339 05/12/2011 11:23
## 5 5 carlitos 1323084232 196328 05/12/2011 11:23
## 6 6 carlitos 1323084232 304277 05/12/2011 11:23
## new_window num_window roll_belt pitch_belt yaw_belt total_accel_belt
## 1 no 11 1.41 8.07 -94.4 3
## 2 no 11 1.41 8.07 -94.4 3
## 3 no 11 1.42 8.07 -94.4 3
## 4 no 12 1.48 8.05 -94.4 3
## 5 no 12 1.48 8.07 -94.4 3
## 6 no 12 1.45 8.06 -94.4 3
## kurtosis_roll_belt kurtosis_picth_belt kurtosis_yaw_belt
## 1 NA NA NA
## 2 NA NA NA
## 3 NA NA NA
## 4 NA NA NA
## 5 NA NA NA
## 6 NA NA NA
## skewness_roll_belt skewness_roll_belt.1 skewness_yaw_belt max_roll_belt
## 1 NA NA NA NA
## 2 NA NA NA NA
## 3 NA NA NA NA
## 4 NA NA NA NA
## 5 NA NA NA NA
## 6 NA NA NA NA
## max_picth_belt max_yaw_belt min_roll_belt min_pitch_belt min_yaw_belt
## 1 NA NA NA NA NA
## 2 NA NA NA NA NA
## 3 NA NA NA NA NA
## 4 NA NA NA NA NA
## 5 NA NA NA NA NA
## 6 NA NA NA NA NA
## amplitude_roll_belt amplitude_pitch_belt amplitude_yaw_belt
## 1 NA NA NA
## 2 NA NA NA
## 3 NA NA NA
## 4 NA NA NA
## 5 NA NA NA
## 6 NA NA NA
## var_total_accel_belt avg_roll_belt stddev_roll_belt var_roll_belt
## 1 NA NA NA NA
## 2 NA NA NA NA
## 3 NA NA NA NA
## 4 NA NA NA NA
## 5 NA NA NA NA
## 6 NA NA NA NA
## avg_pitch_belt stddev_pitch_belt var_pitch_belt avg_yaw_belt
## 1 NA NA NA NA
## 2 NA NA NA NA
## 3 NA NA NA NA
## 4 NA NA NA NA
## 5 NA NA NA NA
## 6 NA NA NA NA
## stddev_yaw_belt var_yaw_belt gyros_belt_x gyros_belt_y gyros_belt_z
## 1 NA NA 0.00 0.00 -0.02
## 2 NA NA 0.02 0.00 -0.02
## 3 NA NA 0.00 0.00 -0.02
## 4 NA NA 0.02 0.00 -0.03
## 5 NA NA 0.02 0.02 -0.02
## 6 NA NA 0.02 0.00 -0.02
## accel_belt_x accel_belt_y accel_belt_z magnet_belt_x magnet_belt_y
## 1 -21 4 22 -3 599
## 2 -22 4 22 -7 608
## 3 -20 5 23 -2 600
## 4 -22 3 21 -6 604
## 5 -21 2 24 -6 600
## 6 -21 4 21 0 603
## magnet_belt_z roll_arm pitch_arm yaw_arm total_accel_arm var_accel_arm
## 1 -313 -128 22.5 -161 34 NA
## 2 -311 -128 22.5 -161 34 NA
## 3 -305 -128 22.5 -161 34 NA
## 4 -310 -128 22.1 -161 34 NA
## 5 -302 -128 22.1 -161 34 NA
## 6 -312 -128 22.0 -161 34 NA
## avg_roll_arm stddev_roll_arm var_roll_arm avg_pitch_arm stddev_pitch_arm
## 1 NA NA NA NA NA
## 2 NA NA NA NA NA
## 3 NA NA NA NA NA
## 4 NA NA NA NA NA
## 5 NA NA NA NA NA
## 6 NA NA NA NA NA
## var_pitch_arm avg_yaw_arm stddev_yaw_arm var_yaw_arm gyros_arm_x
## 1 NA NA NA NA 0.00
## 2 NA NA NA NA 0.02
## 3 NA NA NA NA 0.02
## 4 NA NA NA NA 0.02
## 5 NA NA NA NA 0.00
## 6 NA NA NA NA 0.02
## gyros_arm_y gyros_arm_z accel_arm_x accel_arm_y accel_arm_z magnet_arm_x
## 1 0.00 -0.02 -288 109 -123 -368
## 2 -0.02 -0.02 -290 110 -125 -369
## 3 -0.02 -0.02 -289 110 -126 -368
## 4 -0.03 0.02 -289 111 -123 -372
## 5 -0.03 0.00 -289 111 -123 -374
## 6 -0.03 0.00 -289 111 -122 -369
## magnet_arm_y magnet_arm_z kurtosis_roll_arm kurtosis_picth_arm
## 1 337 516 NA NA
## 2 337 513 NA NA
## 3 344 513 NA NA
## 4 344 512 NA NA
## 5 337 506 NA NA
## 6 342 513 NA NA
## kurtosis_yaw_arm skewness_roll_arm skewness_pitch_arm skewness_yaw_arm
## 1 NA NA NA NA
## 2 NA NA NA NA
## 3 NA NA NA NA
## 4 NA NA NA NA
## 5 NA NA NA NA
## 6 NA NA NA NA
## max_roll_arm max_picth_arm max_yaw_arm min_roll_arm min_pitch_arm
## 1 NA NA NA NA NA
## 2 NA NA NA NA NA
## 3 NA NA NA NA NA
## 4 NA NA NA NA NA
## 5 NA NA NA NA NA
## 6 NA NA NA NA NA
## min_yaw_arm amplitude_roll_arm amplitude_pitch_arm amplitude_yaw_arm
## 1 NA NA NA NA
## 2 NA NA NA NA
## 3 NA NA NA NA
## 4 NA NA NA NA
## 5 NA NA NA NA
## 6 NA NA NA NA
## roll_dumbbell pitch_dumbbell yaw_dumbbell kurtosis_roll_dumbbell
## 1 13.05217 -70.49400 -84.87394 NA
## 2 13.13074 -70.63751 -84.71065 NA
## 3 12.85075 -70.27812 -85.14078 NA
## 4 13.43120 -70.39379 -84.87363 NA
## 5 13.37872 -70.42856 -84.85306 NA
## 6 13.38246 -70.81759 -84.46500 NA
## kurtosis_picth_dumbbell kurtosis_yaw_dumbbell skewness_roll_dumbbell
## 1 NA NA NA
## 2 NA NA NA
## 3 NA NA NA
## 4 NA NA NA
## 5 NA NA NA
## 6 NA NA NA
## skewness_pitch_dumbbell skewness_yaw_dumbbell max_roll_dumbbell
## 1 NA NA NA
## 2 NA NA NA
## 3 NA NA NA
## 4 NA NA NA
## 5 NA NA NA
## 6 NA NA NA
## max_picth_dumbbell max_yaw_dumbbell min_roll_dumbbell min_pitch_dumbbell
## 1 NA NA NA NA
## 2 NA NA NA NA
## 3 NA NA NA NA
## 4 NA NA NA NA
## 5 NA NA NA NA
## 6 NA NA NA NA
## min_yaw_dumbbell amplitude_roll_dumbbell amplitude_pitch_dumbbell
## 1 NA NA NA
## 2 NA NA NA
## 3 NA NA NA
## 4 NA NA NA
## 5 NA NA NA
## 6 NA NA NA
## amplitude_yaw_dumbbell total_accel_dumbbell var_accel_dumbbell
## 1 NA 37 NA
## 2 NA 37 NA
## 3 NA 37 NA
## 4 NA 37 NA
## 5 NA 37 NA
## 6 NA 37 NA
## avg_roll_dumbbell stddev_roll_dumbbell var_roll_dumbbell
## 1 NA NA NA
## 2 NA NA NA
## 3 NA NA NA
## 4 NA NA NA
## 5 NA NA NA
## 6 NA NA NA
## avg_pitch_dumbbell stddev_pitch_dumbbell var_pitch_dumbbell
## 1 NA NA NA
## 2 NA NA NA
## 3 NA NA NA
## 4 NA NA NA
## 5 NA NA NA
## 6 NA NA NA
## avg_yaw_dumbbell stddev_yaw_dumbbell var_yaw_dumbbell gyros_dumbbell_x
## 1 NA NA NA 0
## 2 NA NA NA 0
## 3 NA NA NA 0
## 4 NA NA NA 0
## 5 NA NA NA 0
## 6 NA NA NA 0
## gyros_dumbbell_y gyros_dumbbell_z accel_dumbbell_x accel_dumbbell_y
## 1 -0.02 0.00 -234 47
## 2 -0.02 0.00 -233 47
## 3 -0.02 0.00 -232 46
## 4 -0.02 -0.02 -232 48
## 5 -0.02 0.00 -233 48
## 6 -0.02 0.00 -234 48
## accel_dumbbell_z magnet_dumbbell_x magnet_dumbbell_y magnet_dumbbell_z
## 1 -271 -559 293 -65
## 2 -269 -555 296 -64
## 3 -270 -561 298 -63
## 4 -269 -552 303 -60
## 5 -270 -554 292 -68
## 6 -269 -558 294 -66
## roll_forearm pitch_forearm yaw_forearm kurtosis_roll_forearm
## 1 28.4 -63.9 -153 NA
## 2 28.3 -63.9 -153 NA
## 3 28.3 -63.9 -152 NA
## 4 28.1 -63.9 -152 NA
## 5 28.0 -63.9 -152 NA
## 6 27.9 -63.9 -152 NA
## kurtosis_picth_forearm kurtosis_yaw_forearm skewness_roll_forearm
## 1 NA NA NA
## 2 NA NA NA
## 3 NA NA NA
## 4 NA NA NA
## 5 NA NA NA
## 6 NA NA NA
## skewness_pitch_forearm skewness_yaw_forearm max_roll_forearm
## 1 NA NA NA
## 2 NA NA NA
## 3 NA NA NA
## 4 NA NA NA
## 5 NA NA NA
## 6 NA NA NA
## max_picth_forearm max_yaw_forearm min_roll_forearm min_pitch_forearm
## 1 NA NA NA NA
## 2 NA NA NA NA
## 3 NA NA NA NA
## 4 NA NA NA NA
## 5 NA NA NA NA
## 6 NA NA NA NA
## min_yaw_forearm amplitude_roll_forearm amplitude_pitch_forearm
## 1 NA NA NA
## 2 NA NA NA
## 3 NA NA NA
## 4 NA NA NA
## 5 NA NA NA
## 6 NA NA NA
## amplitude_yaw_forearm total_accel_forearm var_accel_forearm
## 1 NA 36 NA
## 2 NA 36 NA
## 3 NA 36 NA
## 4 NA 36 NA
## 5 NA 36 NA
## 6 NA 36 NA
## avg_roll_forearm stddev_roll_forearm var_roll_forearm avg_pitch_forearm
## 1 NA NA NA NA
## 2 NA NA NA NA
## 3 NA NA NA NA
## 4 NA NA NA NA
## 5 NA NA NA NA
## 6 NA NA NA NA
## stddev_pitch_forearm var_pitch_forearm avg_yaw_forearm
## 1 NA NA NA
## 2 NA NA NA
## 3 NA NA NA
## 4 NA NA NA
## 5 NA NA NA
## 6 NA NA NA
## stddev_yaw_forearm var_yaw_forearm gyros_forearm_x gyros_forearm_y
## 1 NA NA 0.03 0.00
## 2 NA NA 0.02 0.00
## 3 NA NA 0.03 -0.02
## 4 NA NA 0.02 -0.02
## 5 NA NA 0.02 0.00
## 6 NA NA 0.02 -0.02
## gyros_forearm_z accel_forearm_x accel_forearm_y accel_forearm_z
## 1 -0.02 192 203 -215
## 2 -0.02 192 203 -216
## 3 0.00 196 204 -213
## 4 0.00 189 206 -214
## 5 -0.02 189 206 -214
## 6 -0.03 193 203 -215
## magnet_forearm_x magnet_forearm_y magnet_forearm_z classe
## 1 -17 654 476 A
## 2 -18 661 473 A
## 3 -18 658 469 A
## 4 -16 658 469 A
## 5 -17 655 473 A
## 6 -9 660 478 Asummary(training)## X user_name raw_timestamp_part_1 raw_timestamp_part_2
## Min. : 1 adelmo :3892 Min. :1.322e+09 Min. : 294
## 1st Qu.: 4906 carlitos:3112 1st Qu.:1.323e+09 1st Qu.:252912
## Median : 9812 charles :3536 Median :1.323e+09 Median :496380
## Mean : 9812 eurico :3070 Mean :1.323e+09 Mean :500656
## 3rd Qu.:14717 jeremy :3402 3rd Qu.:1.323e+09 3rd Qu.:751891
## Max. :19622 pedro :2610 Max. :1.323e+09 Max. :998801
##
## cvtd_timestamp new_window num_window roll_belt
## 28/11/2011 14:14: 1498 no :19216 Min. : 1.0 Min. :-28.90
## 05/12/2011 11:24: 1497 yes: 406 1st Qu.:222.0 1st Qu.: 1.10
## 30/11/2011 17:11: 1440 Median :424.0 Median :113.00
## 05/12/2011 11:25: 1425 Mean :430.6 Mean : 64.41
## 02/12/2011 14:57: 1380 3rd Qu.:644.0 3rd Qu.:123.00
## 02/12/2011 13:34: 1375 Max. :864.0 Max. :162.00
## (Other) :11007
## pitch_belt yaw_belt total_accel_belt kurtosis_roll_belt
## Min. :-55.8000 Min. :-180.00 Min. : 0.00 Min. :-2.121
## 1st Qu.: 1.7600 1st Qu.: -88.30 1st Qu.: 3.00 1st Qu.:-1.329
## Median : 5.2800 Median : -13.00 Median :17.00 Median :-0.899
## Mean : 0.3053 Mean : -11.21 Mean :11.31 Mean :-0.220
## 3rd Qu.: 14.9000 3rd Qu.: 12.90 3rd Qu.:18.00 3rd Qu.:-0.219
## Max. : 60.3000 Max. : 179.00 Max. :29.00 Max. :33.000
## NA's :19226
## kurtosis_picth_belt kurtosis_yaw_belt skewness_roll_belt
## Min. :-2.190 Mode:logical Min. :-5.745
## 1st Qu.:-1.107 NA's:19622 1st Qu.:-0.444
## Median :-0.151 Median : 0.000
## Mean : 4.334 Mean :-0.026
## 3rd Qu.: 3.178 3rd Qu.: 0.417
## Max. :58.000 Max. : 3.595
## NA's :19248 NA's :19225
## skewness_roll_belt.1 skewness_yaw_belt max_roll_belt max_picth_belt
## Min. :-7.616 Mode:logical Min. :-94.300 Min. : 3.00
## 1st Qu.:-1.114 NA's:19622 1st Qu.:-88.000 1st Qu.: 5.00
## Median :-0.068 Median : -5.100 Median :18.00
## Mean :-0.296 Mean : -6.667 Mean :12.92
## 3rd Qu.: 0.661 3rd Qu.: 18.500 3rd Qu.:19.00
## Max. : 7.348 Max. :180.000 Max. :30.00
## NA's :19248 NA's :19216 NA's :19216
## max_yaw_belt min_roll_belt min_pitch_belt min_yaw_belt
## Min. :-2.10 Min. :-180.00 Min. : 0.00 Min. :-2.10
## 1st Qu.:-1.30 1st Qu.: -88.40 1st Qu.: 3.00 1st Qu.:-1.30
## Median :-0.90 Median : -7.85 Median :16.00 Median :-0.90
## Mean :-0.22 Mean : -10.44 Mean :10.76 Mean :-0.22
## 3rd Qu.:-0.20 3rd Qu.: 9.05 3rd Qu.:17.00 3rd Qu.:-0.20
## Max. :33.00 Max. : 173.00 Max. :23.00 Max. :33.00
## NA's :19226 NA's :19216 NA's :19216 NA's :19226
## amplitude_roll_belt amplitude_pitch_belt amplitude_yaw_belt
## Min. : 0.000 Min. : 0.000 Min. :0
## 1st Qu.: 0.300 1st Qu.: 1.000 1st Qu.:0
## Median : 1.000 Median : 1.000 Median :0
## Mean : 3.769 Mean : 2.167 Mean :0
## 3rd Qu.: 2.083 3rd Qu.: 2.000 3rd Qu.:0
## Max. :360.000 Max. :12.000 Max. :0
## NA's :19216 NA's :19216 NA's :19226
## var_total_accel_belt avg_roll_belt stddev_roll_belt var_roll_belt
## Min. : 0.000 Min. :-27.40 Min. : 0.000 Min. : 0.000
## 1st Qu.: 0.100 1st Qu.: 1.10 1st Qu.: 0.200 1st Qu.: 0.000
## Median : 0.200 Median :116.35 Median : 0.400 Median : 0.100
## Mean : 0.926 Mean : 68.06 Mean : 1.337 Mean : 7.699
## 3rd Qu.: 0.300 3rd Qu.:123.38 3rd Qu.: 0.700 3rd Qu.: 0.500
## Max. :16.500 Max. :157.40 Max. :14.200 Max. :200.700
## NA's :19216 NA's :19216 NA's :19216 NA's :19216
## avg_pitch_belt stddev_pitch_belt var_pitch_belt avg_yaw_belt
## Min. :-51.400 Min. :0.000 Min. : 0.000 Min. :-138.300
## 1st Qu.: 2.025 1st Qu.:0.200 1st Qu.: 0.000 1st Qu.: -88.175
## Median : 5.200 Median :0.400 Median : 0.100 Median : -6.550
## Mean : 0.520 Mean :0.603 Mean : 0.766 Mean : -8.831
## 3rd Qu.: 15.775 3rd Qu.:0.700 3rd Qu.: 0.500 3rd Qu.: 14.125
## Max. : 59.700 Max. :4.000 Max. :16.200 Max. : 173.500
## NA's :19216 NA's :19216 NA's :19216 NA's :19216
## stddev_yaw_belt var_yaw_belt gyros_belt_x
## Min. : 0.000 Min. : 0.000 Min. :-1.040000
## 1st Qu.: 0.100 1st Qu.: 0.010 1st Qu.:-0.030000
## Median : 0.300 Median : 0.090 Median : 0.030000
## Mean : 1.341 Mean : 107.487 Mean :-0.005592
## 3rd Qu.: 0.700 3rd Qu.: 0.475 3rd Qu.: 0.110000
## Max. :176.600 Max. :31183.240 Max. : 2.220000
## NA's :19216 NA's :19216
## gyros_belt_y gyros_belt_z accel_belt_x accel_belt_y
## Min. :-0.64000 Min. :-1.4600 Min. :-120.000 Min. :-69.00
## 1st Qu.: 0.00000 1st Qu.:-0.2000 1st Qu.: -21.000 1st Qu.: 3.00
## Median : 0.02000 Median :-0.1000 Median : -15.000 Median : 35.00
## Mean : 0.03959 Mean :-0.1305 Mean : -5.595 Mean : 30.15
## 3rd Qu.: 0.11000 3rd Qu.:-0.0200 3rd Qu.: -5.000 3rd Qu.: 61.00
## Max. : 0.64000 Max. : 1.6200 Max. : 85.000 Max. :164.00
##
## accel_belt_z magnet_belt_x magnet_belt_y magnet_belt_z
## Min. :-275.00 Min. :-52.0 Min. :354.0 Min. :-623.0
## 1st Qu.:-162.00 1st Qu.: 9.0 1st Qu.:581.0 1st Qu.:-375.0
## Median :-152.00 Median : 35.0 Median :601.0 Median :-320.0
## Mean : -72.59 Mean : 55.6 Mean :593.7 Mean :-345.5
## 3rd Qu.: 27.00 3rd Qu.: 59.0 3rd Qu.:610.0 3rd Qu.:-306.0
## Max. : 105.00 Max. :485.0 Max. :673.0 Max. : 293.0
##
## roll_arm pitch_arm yaw_arm total_accel_arm
## Min. :-180.00 Min. :-88.800 Min. :-180.0000 Min. : 1.00
## 1st Qu.: -31.77 1st Qu.:-25.900 1st Qu.: -43.1000 1st Qu.:17.00
## Median : 0.00 Median : 0.000 Median : 0.0000 Median :27.00
## Mean : 17.83 Mean : -4.612 Mean : -0.6188 Mean :25.51
## 3rd Qu.: 77.30 3rd Qu.: 11.200 3rd Qu.: 45.8750 3rd Qu.:33.00
## Max. : 180.00 Max. : 88.500 Max. : 180.0000 Max. :66.00
##
## var_accel_arm avg_roll_arm stddev_roll_arm var_roll_arm
## Min. : 0.00 Min. :-166.67 Min. : 0.000 Min. : 0.000
## 1st Qu.: 9.03 1st Qu.: -38.37 1st Qu.: 1.376 1st Qu.: 1.898
## Median : 40.61 Median : 0.00 Median : 5.702 Median : 32.517
## Mean : 53.23 Mean : 12.68 Mean : 11.201 Mean : 417.264
## 3rd Qu.: 75.62 3rd Qu.: 76.33 3rd Qu.: 14.921 3rd Qu.: 222.647
## Max. :331.70 Max. : 163.33 Max. :161.964 Max. :26232.208
## NA's :19216 NA's :19216 NA's :19216 NA's :19216
## avg_pitch_arm stddev_pitch_arm var_pitch_arm avg_yaw_arm
## Min. :-81.773 Min. : 0.000 Min. : 0.000 Min. :-173.440
## 1st Qu.:-22.770 1st Qu.: 1.642 1st Qu.: 2.697 1st Qu.: -29.198
## Median : 0.000 Median : 8.133 Median : 66.146 Median : 0.000
## Mean : -4.901 Mean :10.383 Mean : 195.864 Mean : 2.359
## 3rd Qu.: 8.277 3rd Qu.:16.327 3rd Qu.: 266.576 3rd Qu.: 38.185
## Max. : 75.659 Max. :43.412 Max. :1884.565 Max. : 152.000
## NA's :19216 NA's :19216 NA's :19216 NA's :19216
## stddev_yaw_arm var_yaw_arm gyros_arm_x
## Min. : 0.000 Min. : 0.000 Min. :-6.37000
## 1st Qu.: 2.577 1st Qu.: 6.642 1st Qu.:-1.33000
## Median : 16.682 Median : 278.309 Median : 0.08000
## Mean : 22.270 Mean : 1055.933 Mean : 0.04277
## 3rd Qu.: 35.984 3rd Qu.: 1294.850 3rd Qu.: 1.57000
## Max. :177.044 Max. :31344.568 Max. : 4.87000
## NA's :19216 NA's :19216
## gyros_arm_y gyros_arm_z accel_arm_x accel_arm_y
## Min. :-3.4400 Min. :-2.3300 Min. :-404.00 Min. :-318.0
## 1st Qu.:-0.8000 1st Qu.:-0.0700 1st Qu.:-242.00 1st Qu.: -54.0
## Median :-0.2400 Median : 0.2300 Median : -44.00 Median : 14.0
## Mean :-0.2571 Mean : 0.2695 Mean : -60.24 Mean : 32.6
## 3rd Qu.: 0.1400 3rd Qu.: 0.7200 3rd Qu.: 84.00 3rd Qu.: 139.0
## Max. : 2.8400 Max. : 3.0200 Max. : 437.00 Max. : 308.0
##
## accel_arm_z magnet_arm_x magnet_arm_y magnet_arm_z
## Min. :-636.00 Min. :-584.0 Min. :-392.0 Min. :-597.0
## 1st Qu.:-143.00 1st Qu.:-300.0 1st Qu.: -9.0 1st Qu.: 131.2
## Median : -47.00 Median : 289.0 Median : 202.0 Median : 444.0
## Mean : -71.25 Mean : 191.7 Mean : 156.6 Mean : 306.5
## 3rd Qu.: 23.00 3rd Qu.: 637.0 3rd Qu.: 323.0 3rd Qu.: 545.0
## Max. : 292.00 Max. : 782.0 Max. : 583.0 Max. : 694.0
##
## kurtosis_roll_arm kurtosis_picth_arm kurtosis_yaw_arm skewness_roll_arm
## Min. :-1.809 Min. :-2.084 Min. :-2.103 Min. :-2.541
## 1st Qu.:-1.345 1st Qu.:-1.280 1st Qu.:-1.220 1st Qu.:-0.561
## Median :-0.894 Median :-1.010 Median :-0.733 Median : 0.040
## Mean :-0.366 Mean :-0.542 Mean : 0.406 Mean : 0.068
## 3rd Qu.:-0.038 3rd Qu.:-0.379 3rd Qu.: 0.115 3rd Qu.: 0.671
## Max. :21.456 Max. :19.751 Max. :56.000 Max. : 4.394
## NA's :19294 NA's :19296 NA's :19227 NA's :19293
## skewness_pitch_arm skewness_yaw_arm max_roll_arm max_picth_arm
## Min. :-4.565 Min. :-6.708 Min. :-73.100 Min. :-173.000
## 1st Qu.:-0.618 1st Qu.:-0.743 1st Qu.: -0.175 1st Qu.: -1.975
## Median :-0.035 Median :-0.133 Median : 4.950 Median : 23.250
## Mean :-0.065 Mean :-0.229 Mean : 11.236 Mean : 35.751
## 3rd Qu.: 0.454 3rd Qu.: 0.344 3rd Qu.: 26.775 3rd Qu.: 95.975
## Max. : 3.043 Max. : 7.483 Max. : 85.500 Max. : 180.000
## NA's :19296 NA's :19227 NA's :19216 NA's :19216
## max_yaw_arm min_roll_arm min_pitch_arm min_yaw_arm
## Min. : 4.00 Min. :-89.10 Min. :-180.00 Min. : 1.00
## 1st Qu.:29.00 1st Qu.:-41.98 1st Qu.: -72.62 1st Qu.: 8.00
## Median :34.00 Median :-22.45 Median : -33.85 Median :13.00
## Mean :35.46 Mean :-21.22 Mean : -33.92 Mean :14.66
## 3rd Qu.:41.00 3rd Qu.: 0.00 3rd Qu.: 0.00 3rd Qu.:19.00
## Max. :65.00 Max. : 66.40 Max. : 152.00 Max. :38.00
## NA's :19216 NA's :19216 NA's :19216 NA's :19216
## amplitude_roll_arm amplitude_pitch_arm amplitude_yaw_arm
## Min. : 0.000 Min. : 0.000 Min. : 0.00
## 1st Qu.: 5.425 1st Qu.: 9.925 1st Qu.:13.00
## Median : 28.450 Median : 54.900 Median :22.00
## Mean : 32.452 Mean : 69.677 Mean :20.79
## 3rd Qu.: 50.960 3rd Qu.:115.175 3rd Qu.:28.75
## Max. :119.500 Max. :360.000 Max. :52.00
## NA's :19216 NA's :19216 NA's :19216
## roll_dumbbell pitch_dumbbell yaw_dumbbell
## Min. :-153.71 Min. :-149.59 Min. :-150.871
## 1st Qu.: -18.49 1st Qu.: -40.89 1st Qu.: -77.644
## Median : 48.17 Median : -20.96 Median : -3.324
## Mean : 23.84 Mean : -10.78 Mean : 1.674
## 3rd Qu.: 67.61 3rd Qu.: 17.50 3rd Qu.: 79.643
## Max. : 153.55 Max. : 149.40 Max. : 154.952
##
## kurtosis_roll_dumbbell kurtosis_picth_dumbbell kurtosis_yaw_dumbbell
## Min. :-2.174 Min. :-2.200 Mode:logical
## 1st Qu.:-0.682 1st Qu.:-0.721 NA's:19622
## Median :-0.033 Median :-0.133
## Mean : 0.452 Mean : 0.286
## 3rd Qu.: 0.940 3rd Qu.: 0.584
## Max. :54.998 Max. :55.628
## NA's :19221 NA's :19218
## skewness_roll_dumbbell skewness_pitch_dumbbell skewness_yaw_dumbbell
## Min. :-7.384 Min. :-7.447 Mode:logical
## 1st Qu.:-0.581 1st Qu.:-0.526 NA's:19622
## Median :-0.076 Median :-0.091
## Mean :-0.115 Mean :-0.035
## 3rd Qu.: 0.400 3rd Qu.: 0.505
## Max. : 1.958 Max. : 3.769
## NA's :19220 NA's :19217
## max_roll_dumbbell max_picth_dumbbell max_yaw_dumbbell min_roll_dumbbell
## Min. :-70.10 Min. :-112.90 Min. :-2.20 Min. :-149.60
## 1st Qu.:-27.15 1st Qu.: -66.70 1st Qu.:-0.70 1st Qu.: -59.67
## Median : 14.85 Median : 40.05 Median : 0.00 Median : -43.55
## Mean : 13.76 Mean : 32.75 Mean : 0.45 Mean : -41.24
## 3rd Qu.: 50.58 3rd Qu.: 133.22 3rd Qu.: 0.90 3rd Qu.: -25.20
## Max. :137.00 Max. : 155.00 Max. :55.00 Max. : 73.20
## NA's :19216 NA's :19216 NA's :19221 NA's :19216
## min_pitch_dumbbell min_yaw_dumbbell amplitude_roll_dumbbell
## Min. :-147.00 Min. :-2.20 Min. : 0.00
## 1st Qu.: -91.80 1st Qu.:-0.70 1st Qu.: 14.97
## Median : -66.15 Median : 0.00 Median : 35.05
## Mean : -33.18 Mean : 0.45 Mean : 55.00
## 3rd Qu.: 21.20 3rd Qu.: 0.90 3rd Qu.: 81.04
## Max. : 120.90 Max. :55.00 Max. :256.48
## NA's :19216 NA's :19221 NA's :19216
## amplitude_pitch_dumbbell amplitude_yaw_dumbbell total_accel_dumbbell
## Min. : 0.00 Min. :0 Min. : 0.00
## 1st Qu.: 17.06 1st Qu.:0 1st Qu.: 4.00
## Median : 41.73 Median :0 Median :10.00
## Mean : 65.93 Mean :0 Mean :13.72
## 3rd Qu.: 99.55 3rd Qu.:0 3rd Qu.:19.00
## Max. :273.59 Max. :0 Max. :58.00
## NA's :19216 NA's :19221
## var_accel_dumbbell avg_roll_dumbbell stddev_roll_dumbbell
## Min. : 0.000 Min. :-128.96 Min. : 0.000
## 1st Qu.: 0.378 1st Qu.: -12.33 1st Qu.: 4.639
## Median : 1.000 Median : 48.23 Median : 12.204
## Mean : 4.388 Mean : 23.86 Mean : 20.761
## 3rd Qu.: 3.434 3rd Qu.: 64.37 3rd Qu.: 26.356
## Max. :230.428 Max. : 125.99 Max. :123.778
## NA's :19216 NA's :19216 NA's :19216
## var_roll_dumbbell avg_pitch_dumbbell stddev_pitch_dumbbell
## Min. : 0.00 Min. :-70.73 Min. : 0.000
## 1st Qu.: 21.52 1st Qu.:-42.00 1st Qu.: 3.482
## Median : 148.95 Median :-19.91 Median : 8.089
## Mean : 1020.27 Mean :-12.33 Mean :13.147
## 3rd Qu.: 694.65 3rd Qu.: 13.21 3rd Qu.:19.238
## Max. :15321.01 Max. : 94.28 Max. :82.680
## NA's :19216 NA's :19216 NA's :19216
## var_pitch_dumbbell avg_yaw_dumbbell stddev_yaw_dumbbell
## Min. : 0.00 Min. :-117.950 Min. : 0.000
## 1st Qu.: 12.12 1st Qu.: -76.696 1st Qu.: 3.885
## Median : 65.44 Median : -4.505 Median : 10.264
## Mean : 350.31 Mean : 0.202 Mean : 16.647
## 3rd Qu.: 370.11 3rd Qu.: 71.234 3rd Qu.: 24.674
## Max. :6836.02 Max. : 134.905 Max. :107.088
## NA's :19216 NA's :19216 NA's :19216
## var_yaw_dumbbell gyros_dumbbell_x gyros_dumbbell_y
## Min. : 0.00 Min. :-204.0000 Min. :-2.10000
## 1st Qu.: 15.09 1st Qu.: -0.0300 1st Qu.:-0.14000
## Median : 105.35 Median : 0.1300 Median : 0.03000
## Mean : 589.84 Mean : 0.1611 Mean : 0.04606
## 3rd Qu.: 608.79 3rd Qu.: 0.3500 3rd Qu.: 0.21000
## Max. :11467.91 Max. : 2.2200 Max. :52.00000
## NA's :19216
## gyros_dumbbell_z accel_dumbbell_x accel_dumbbell_y accel_dumbbell_z
## Min. : -2.380 Min. :-419.00 Min. :-189.00 Min. :-334.00
## 1st Qu.: -0.310 1st Qu.: -50.00 1st Qu.: -8.00 1st Qu.:-142.00
## Median : -0.130 Median : -8.00 Median : 41.50 Median : -1.00
## Mean : -0.129 Mean : -28.62 Mean : 52.63 Mean : -38.32
## 3rd Qu.: 0.030 3rd Qu.: 11.00 3rd Qu.: 111.00 3rd Qu.: 38.00
## Max. :317.000 Max. : 235.00 Max. : 315.00 Max. : 318.00
##
## magnet_dumbbell_x magnet_dumbbell_y magnet_dumbbell_z roll_forearm
## Min. :-643.0 Min. :-3600 Min. :-262.00 Min. :-180.0000
## 1st Qu.:-535.0 1st Qu.: 231 1st Qu.: -45.00 1st Qu.: -0.7375
## Median :-479.0 Median : 311 Median : 13.00 Median : 21.7000
## Mean :-328.5 Mean : 221 Mean : 46.05 Mean : 33.8265
## 3rd Qu.:-304.0 3rd Qu.: 390 3rd Qu.: 95.00 3rd Qu.: 140.0000
## Max. : 592.0 Max. : 633 Max. : 452.00 Max. : 180.0000
##
## pitch_forearm yaw_forearm kurtosis_roll_forearm
## Min. :-72.50 Min. :-180.00 Min. :-1.879
## 1st Qu.: 0.00 1st Qu.: -68.60 1st Qu.:-1.398
## Median : 9.24 Median : 0.00 Median :-1.119
## Mean : 10.71 Mean : 19.21 Mean :-0.689
## 3rd Qu.: 28.40 3rd Qu.: 110.00 3rd Qu.:-0.618
## Max. : 89.80 Max. : 180.00 Max. :40.060
## NA's :19300
## kurtosis_picth_forearm kurtosis_yaw_forearm skewness_roll_forearm
## Min. :-2.098 Mode:logical Min. :-2.297
## 1st Qu.:-1.376 NA's:19622 1st Qu.:-0.402
## Median :-0.890 Median : 0.003
## Mean : 0.419 Mean :-0.009
## 3rd Qu.: 0.054 3rd Qu.: 0.370
## Max. :33.626 Max. : 5.856
## NA's :19301 NA's :19299
## skewness_pitch_forearm skewness_yaw_forearm max_roll_forearm
## Min. :-5.241 Mode:logical Min. :-66.60
## 1st Qu.:-0.881 NA's:19622 1st Qu.: 0.00
## Median :-0.156 Median : 26.80
## Mean :-0.223 Mean : 24.49
## 3rd Qu.: 0.514 3rd Qu.: 45.95
## Max. : 4.464 Max. : 89.80
## NA's :19301 NA's :19216
## max_picth_forearm max_yaw_forearm min_roll_forearm min_pitch_forearm
## Min. :-151.00 Min. :-1.900 Min. :-72.500 Min. :-180.00
## 1st Qu.: 0.00 1st Qu.:-1.400 1st Qu.: -6.075 1st Qu.:-175.00
## Median : 113.00 Median :-1.100 Median : 0.000 Median : -61.00
## Mean : 81.49 Mean :-0.689 Mean : -0.167 Mean : -57.57
## 3rd Qu.: 174.75 3rd Qu.:-0.600 3rd Qu.: 12.075 3rd Qu.: 0.00
## Max. : 180.00 Max. :40.100 Max. : 62.100 Max. : 167.00
## NA's :19216 NA's :19300 NA's :19216 NA's :19216
## min_yaw_forearm amplitude_roll_forearm amplitude_pitch_forearm
## Min. :-1.900 Min. : 0.000 Min. : 0.0
## 1st Qu.:-1.400 1st Qu.: 1.125 1st Qu.: 2.0
## Median :-1.100 Median : 17.770 Median : 83.7
## Mean :-0.689 Mean : 24.653 Mean :139.1
## 3rd Qu.:-0.600 3rd Qu.: 39.875 3rd Qu.:350.0
## Max. :40.100 Max. :126.000 Max. :360.0
## NA's :19300 NA's :19216 NA's :19216
## amplitude_yaw_forearm total_accel_forearm var_accel_forearm
## Min. :0 Min. : 0.00 Min. : 0.000
## 1st Qu.:0 1st Qu.: 29.00 1st Qu.: 6.759
## Median :0 Median : 36.00 Median : 21.165
## Mean :0 Mean : 34.72 Mean : 33.502
## 3rd Qu.:0 3rd Qu.: 41.00 3rd Qu.: 51.240
## Max. :0 Max. :108.00 Max. :172.606
## NA's :19300 NA's :19216
## avg_roll_forearm stddev_roll_forearm var_roll_forearm
## Min. :-177.234 Min. : 0.000 Min. : 0.00
## 1st Qu.: -0.909 1st Qu.: 0.428 1st Qu.: 0.18
## Median : 11.172 Median : 8.030 Median : 64.48
## Mean : 33.165 Mean : 41.986 Mean : 5274.10
## 3rd Qu.: 107.132 3rd Qu.: 85.373 3rd Qu.: 7289.08
## Max. : 177.256 Max. :179.171 Max. :32102.24
## NA's :19216 NA's :19216 NA's :19216
## avg_pitch_forearm stddev_pitch_forearm var_pitch_forearm
## Min. :-68.17 Min. : 0.000 Min. : 0.000
## 1st Qu.: 0.00 1st Qu.: 0.336 1st Qu.: 0.113
## Median : 12.02 Median : 5.516 Median : 30.425
## Mean : 11.79 Mean : 7.977 Mean : 139.593
## 3rd Qu.: 28.48 3rd Qu.:12.866 3rd Qu.: 165.532
## Max. : 72.09 Max. :47.745 Max. :2279.617
## NA's :19216 NA's :19216 NA's :19216
## avg_yaw_forearm stddev_yaw_forearm var_yaw_forearm gyros_forearm_x
## Min. :-155.06 Min. : 0.000 Min. : 0.00 Min. :-22.000
## 1st Qu.: -26.26 1st Qu.: 0.524 1st Qu.: 0.27 1st Qu.: -0.220
## Median : 0.00 Median : 24.743 Median : 612.21 Median : 0.050
## Mean : 18.00 Mean : 44.854 Mean : 4639.85 Mean : 0.158
## 3rd Qu.: 85.79 3rd Qu.: 85.817 3rd Qu.: 7368.41 3rd Qu.: 0.560
## Max. : 169.24 Max. :197.508 Max. :39009.33 Max. : 3.970
## NA's :19216 NA's :19216 NA's :19216
## gyros_forearm_y gyros_forearm_z accel_forearm_x accel_forearm_y
## Min. : -7.02000 Min. : -8.0900 Min. :-498.00 Min. :-632.0
## 1st Qu.: -1.46000 1st Qu.: -0.1800 1st Qu.:-178.00 1st Qu.: 57.0
## Median : 0.03000 Median : 0.0800 Median : -57.00 Median : 201.0
## Mean : 0.07517 Mean : 0.1512 Mean : -61.65 Mean : 163.7
## 3rd Qu.: 1.62000 3rd Qu.: 0.4900 3rd Qu.: 76.00 3rd Qu.: 312.0
## Max. :311.00000 Max. :231.0000 Max. : 477.00 Max. : 923.0
##
## accel_forearm_z magnet_forearm_x magnet_forearm_y magnet_forearm_z
## Min. :-446.00 Min. :-1280.0 Min. :-896.0 Min. :-973.0
## 1st Qu.:-182.00 1st Qu.: -616.0 1st Qu.: 2.0 1st Qu.: 191.0
## Median : -39.00 Median : -378.0 Median : 591.0 Median : 511.0
## Mean : -55.29 Mean : -312.6 Mean : 380.1 Mean : 393.6
## 3rd Qu.: 26.00 3rd Qu.: -73.0 3rd Qu.: 737.0 3rd Qu.: 653.0
## Max. : 291.00 Max. : 672.0 Max. :1480.0 Max. :1090.0
##
## classe
## A:5580
## B:3797
## C:3422
## D:3216
## E:3607
##
## - As we can see, the first 7 columns are irrelavant to the analysis. So just remove them.
training = training[,-c(1:7)]
testing = testing[,-c(1:7)]- Delete all empty columns
training = training[,colSums(is.na(training)) == 0]
testing = testing[,colSums(is.na(testing)) == 0]Model Selection
- Partition training set into trainging set and validation set
partition <- createDataPartition(y=training$classe, p=0.75, list=FALSE)
trainingset <- training[partition, ]
validatingset <- training[-partition, ]Have a look at the training set
plot(trainingset$classe, main="levels of variable classe in trainingset data set")
Firstly, we try to use decision tree to build the model
model1 <- rpart(classe ~ ., data=trainingset, method="class")
prediction1 <- predict(model1, validatingset, type = "class")
confusionMatrix(prediction1, validatingset$classe)## Confusion Matrix and Statistics
##
## Reference
## Prediction A B C D E
## A 1264 152 47 87 19
## B 48 565 92 72 96
## C 32 104 612 76 79
## D 31 73 71 467 51
## E 20 55 33 102 656
##
## Overall Statistics
##
## Accuracy : 0.7268
## 95% CI : (0.714, 0.7392)
## No Information Rate : 0.2845
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.6527
## Mcnemar's Test P-Value : < 2.2e-16
##
## Statistics by Class:
##
## Class: A Class: B Class: C Class: D Class: E
## Sensitivity 0.9061 0.5954 0.7158 0.58085 0.7281
## Specificity 0.9131 0.9221 0.9281 0.94488 0.9475
## Pos Pred Value 0.8056 0.6472 0.6777 0.67388 0.7575
## Neg Pred Value 0.9607 0.9047 0.9393 0.91997 0.9393
## Prevalence 0.2845 0.1935 0.1743 0.16395 0.1837
## Detection Rate 0.2577 0.1152 0.1248 0.09523 0.1338
## Detection Prevalence 0.3199 0.1780 0.1841 0.14131 0.1766
## Balanced Accuracy 0.9096 0.7587 0.8220 0.76286 0.8378It seems like the accuracy does not reach our expectation by using decision tree model. Let’s try random forest model then
model2 <- randomForest(classe ~. , data=trainingset, method="class")
prediction2 <- predict(model2, validatingset, type = "class")
confusionMatrix(prediction2, validatingset$classe)## Confusion Matrix and Statistics
##
## Reference
## Prediction A B C D E
## A 1393 6 0 0 0
## B 2 941 8 0 0
## C 0 2 847 9 0
## D 0 0 0 794 4
## E 0 0 0 1 897
##
## Overall Statistics
##
## Accuracy : 0.9935
## 95% CI : (0.9908, 0.9955)
## No Information Rate : 0.2845
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.9917
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: A Class: B Class: C Class: D Class: E
## Sensitivity 0.9986 0.9916 0.9906 0.9876 0.9956
## Specificity 0.9983 0.9975 0.9973 0.9990 0.9998
## Pos Pred Value 0.9957 0.9895 0.9872 0.9950 0.9989
## Neg Pred Value 0.9994 0.9980 0.9980 0.9976 0.9990
## Prevalence 0.2845 0.1935 0.1743 0.1639 0.1837
## Detection Rate 0.2841 0.1919 0.1727 0.1619 0.1829
## Detection Prevalence 0.2853 0.1939 0.1750 0.1627 0.1831
## Balanced Accuracy 0.9984 0.9945 0.9940 0.9933 0.9977Splendid!
Apply the random forsest model to the testing set.
predictfinal <- predict(model2, testing, type="class")
predictfinal## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## B A B A A E D B A A B C B A E E A B B B
## Levels: A B C D E