Feature Importance of XGBoost
=============================

The feature importance analysis for the XGBoost model highlights the relative contribution of each feature to model predictions.  
Below table lists all 88 variables along with their importance, cumulative importance, and rank for XGBoost in RECLAIM.

.. list-table:: **Feature importance of all 88 variables from XGBoost.**
   :header-rows: 1
   :align: center
   :widths: 5 20 20 20

   * - Rank
     - Variable
     - Feature Importance (%)
     - Cumulative Importance (%)
   * - 1
     - log_OBC
     - 25.580140
     - 25.580140
   * - 2
     - log_LCWB
     - 18.123307
     - 43.703447
   * - 3
     - log_CA
     - 12.262684
     - 55.966131
   * - 4
     - log_LCM
     - 5.976027
     - 61.942159
   * - 5
     - log_LCG
     - 5.152744
     - 67.094903
   * - 6
     - log_LCSG
     - 4.975100
     - 72.070003
   * - 7
     - log_LCC
     - 1.642522
     - 73.712525
   * - 8
     - log_LCS
     - 1.506769
     - 75.219294
   * - 9
     - log_SA_std
     - 1.341006
     - 76.560301
   * - 10
     - log_O_std
     - 1.127022
     - 77.687323
   * - 11
     - log_LCT
     - 1.101582
     - 78.788904
   * - 12
     - log_SA_mean
     - 1.008979
     - 79.797883
   * - 13
     - log_LCHV
     - 0.887762
     - 80.685645
   * - 14
     - log_LCAS
     - 0.792153
     - 81.477799
   * - 15
     - log_LCBS
     - 0.718496
     - 82.196295
   * - 16
     - log_RP
     - 0.714475
     - 82.910770
   * - 17
     - log_rain_per_area
     - 0.667992
     - 83.578762
   * - 18
     - R_SA_cap
     - 0.602455
     - 84.181217
   * - 19
     - SLOP
     - 0.579330
     - 84.760547
   * - 20
     - NSSC1_cv
     - 0.557334
     - 85.317881
   * - 21
     - SA_skew
     - 0.520467
     - 85.838348
   * - 22
     - log_DCA
     - 0.514445
     - 86.352793
   * - 23
     - MRB
     - 0.478671
     - 86.831465
   * - 24
     - log_MAI
     - 0.433758
     - 87.265223
   * - 25
     - log_FL
     - 0.400659
     - 87.665882
   * - 26
     - DLC
     - 0.385051
     - 88.050933
   * - 27
     - NSSC1_std
     - 0.383057
     - 88.433989
   * - 28
     - log_RA
     - 0.350518
     - 88.784507
   * - 29
     - R_shrub_bare
     - 0.332395
     - 89.116902
   * - 30
     - log_SOUT
     - 0.318822
     - 89.435724
   * - 31
     - R_coarse_sand
     - 0.303878
     - 89.739602
   * - 32
     - AGE
     - 0.302968
     - 90.042569
   * - 33
     - log_MAO
     - 0.301705
     - 90.344274
   * - 34
     - wind_std
     - 0.290478
     - 90.634752
   * - 35
     - LON
     - 0.289763
     - 90.924515
   * - 36
     - log_SA_mean_clip
     - 0.288825
     - 91.213340
   * - 37
     - ASP
     - 0.286191
     - 91.499531
   * - 38
     - SA_cv
     - 0.283685
     - 91.783217
   * - 39
     - log_PAI
     - 0.262242
     - 92.045458
   * - 40
     - E_std
     - 0.259516
     - 92.304975
   * - 41
     - I_cv
     - 0.231728
     - 92.536703
   * - 42
     - wind_cv
     - 0.230122
     - 92.766825
   * - 43
     - COAR
     - 0.213779
     - 92.980605
   * - 44
     - #_rain_above_100
     - 0.211475
     - 93.192080
   * - 45
     - #_rain_above_10
     - 0.211080
     - 93.403159
   * - 46
     - NSSC2_max_persis
     - 0.210585
     - 93.613745
   * - 47
     - log_ESR
     - 0.202541
     - 93.816285
   * - 48
     - NSSC1_skew
     - 0.201005
     - 94.017290
   * - 49
     - ELEV
     - 0.200103
     - 94.217393
   * - 50
     - NVGF
     - 0.199504
     - 94.416897
   * - 51
     - NSSC1_kurt
     - 0.196393
     - 94.613291
   * - 52
     - log_LCSV
     - 0.194322
     - 94.807613
   * - 53
     - SA_above_90
     - 0.183946
     - 94.991559
   * - 54
     - NSSC2_mean
     - 0.183660
     - 95.175219
   * - 55
     - #_rain_above_50
     - 0.180766
     - 95.355984
   * - 56
     - wind_skew
     - 0.176269
     - 95.532254
   * - 57
     - AECC
     - 0.174868
     - 95.707121
   * - 58
     - rel_SA_mean_clip
     - 0.172370
     - 95.879491
   * - 59
     - wind_mean
     - 0.172309
     - 96.051800
   * - 60
     - wind_kurt
     - 0.168957
     - 96.220757
   * - 61
     - O_cv
     - 0.168843
     - 96.389600
   * - 62
     - R_treaa_bare
     - 0.168720
     - 96.558320
   * - 63
     - CURV
     - 0.165235
     - 96.723555
   * - 64
     - SAND
     - 0.158673
     - 96.882228
   * - 65
     - SILT
     - 0.156815
     - 97.039043
   * - 66
     - NSSC1_mean
     - 0.156760
     - 97.195803
   * - 67
     - log_ROBC
     - 0.153572
     - 97.349375
   * - 68
     - I_max_persis
     - 0.152358
     - 97.501733
   * - 69
     - I_above_90
     - 0.151440
     - 97.653172
   * - 70
     - AECS
     - 0.148747
     - 97.801919
   * - 71
     - log_MAR
     - 0.146104
     - 97.948023
   * - 72
     - HILL
     - 0.144328
     - 98.092351
   * - 73
     - CLAY
     - 0.143629
     - 98.235980
   * - 74
     - log_HGT
     - 0.141741
     - 98.377721
   * - 75
     - log_SIN
     - 0.137931
     - 98.515653
   * - 76
     - log_ECLR
     - 0.137038
     - 98.652691
   * - 77
     - tmin_mean
     - 0.126585
     - 98.779275
   * - 78
     - log_TE
     - 0.125490
     - 98.904765
   * - 79
     - log_I_std
     - 0.123198
     - 99.027963
   * - 80
     - BULK
     - 0.121505
     - 99.149468
   * - 81
     - NSSC2_above_90
     - 0.120844
     - 99.270313
   * - 82
     - tmax_mean
     - 0.114328
     - 99.384641
   * - 83
     - log_GC
     - 0.113850
     - 99.498491
   * - 84
     - log_SA_kurt
     - 0.105192
     - 99.603683
   * - 85
     - LAT
     - 0.103628
     - 99.707311
   * - 86
     - log_RT
     - 0.100726
     - 99.808037
   * - 87
     - E_mean
     - 0.098133
     - 99.906170
   * - 88
     - AECI
     - 0.093830
     - 100.000000