svm regression with caret tune, no crossvalidation

8 files changed, 165 insertions, 151 deletions

diff --git a/data/combined-test-predictions.csv b/data/combined-test-predictions.csv
index a39bc69..27666a9 100644
--- a/data/combined-test-predictions.csv
+++ b/data/combined-test-predictions.csv
@@ -1,151 +1,151 @@
 SMILES,LOAEL_measured_median,LOAEL_predicted,Confidence,Dataset
-N#Cc1nn(c(c1S(=O)C(F)(F)F)N)c1c(Cl)cc(cc1Cl)C(F)(F)F,0.00013611,0.04202666947504676,0.7272727272727273,combined-prediction
-OC(=O)C(Oc1ccc(cc1)Oc1ncc(cc1Cl)C(F)(F)F)C,0.00027647,0.03837316659754307,0.6521739130434783,combined-prediction
-CCOP(=S)(SCSC(C)(C)C)OCC,0.00027736000000000004,0.006244785277908732,0.5454545454545454,combined-prediction
-CCSCSP(=S)(OCC)OCC,0.00061449,0.0033397489227135033,0.5454545454545454,combined-prediction
-CCOP(=O)(SC(CC)C)SC(CC)C,0.000872805,0.004760493760561179,0.46153846153846156,combined-prediction
-CNC(=O)CSP(=S)(OC)OC,0.0010905,0.008598461399213199,0.2222222222222222,combined-prediction
-COP(=O)(SC)N,0.0020549,0.07267302761993463,0.13333333333333333,combined-prediction
-CSc1ccc(cc1C)OP(=S)(OC)OC,0.00210185,0.007885803202315566,0.45,combined-prediction
-CCOP(=S)(Oc1ccc2c(c1)oc(=O)c(c2C)Cl)OCC,0.0033631,0.008074684367671859,0.34782608695652173,combined-prediction
-CCOP(=S)(Oc1ncn(n1)c1ccccc1)OCC,0.0041492,0.019419668559497557,0.3333333333333333,combined-prediction
-COc1sc(=O)n(n1)CSP(=S)(OC)OC,0.00471335,0.014453233387553464,0.25,combined-prediction
-CCOP(=S)(OCC)SCSP(=S)(OCC)OCC,0.0049418,0.003882603616523481,0.5454545454545454,combined-prediction
-CCOP(=O)(Oc1ccc(c(c1)C)SC)NC(C)C,0.0049447,0.00588887528527483,0.391304347826087,combined-prediction
-CC(Cc1ccc(cc1)C(C)(C)C)CN1CC(C)OC(C1)C,0.0056016,0.09684939846922258,0.5882352941176471,combined-prediction
-COP(=S)(Oc1nc(Cl)c(cc1Cl)Cl)OC,0.00620095,0.01263784329125101,0.6875,combined-prediction
-OC(C(Cl)(Cl)Cl)(c1ccc(cc1)Cl)c1ccc(cc1)Cl,0.0067479,0.06035236375493807,0.4166666666666667,combined-prediction
-COC(=O)N(C(=O)N1COC2(C(=N1)c1ccc(cc1C2)Cl)C(=O)OC)c1ccc(cc1)OC(F)(F)F,0.0068203,0.06690498702032557,0.25,combined-prediction
-Clc1ccc(cc1)C(c1ccccc1Cl)(c1cncnc1)O,0.0075484,0.06510030909231854,0.7647058823529411,combined-prediction
-COP(=S)(SCn1nnc2c(c1=O)cccc2)OC,0.0076105,0.02533556283830024,0.25,combined-prediction
-N#CC(c1cccc(c1)Oc1ccccc1)OC(=O)C1C(C1(C)C)C=C(Br)Br,0.00781875,0.05246941081941809,0.7391304347826086,combined-prediction
-CCN(c1nc(cc(n1)C)OP(=S)(OC)OC)CC,0.0081878,0.011238266231223978,0.30434782608695654,combined-prediction
-CCCCOC(=O)C(Oc1ccc(cc1)Oc1ccc(cn1)C(F)(F)F)C,0.00885585,0.04770077107958393,0.5,combined-prediction
-COP(=O)(OC=C(Cl)Cl)OC,0.0100688,0.012690525889265763,0.25,combined-prediction
-CCCSP(=O)(SCCC)OCC,0.010069,0.0026313189577840735,0.46153846153846156,combined-prediction
-O=S1OCC2C(CO1)C1(C(C2(Cl)C(=C1Cl)Cl)(Cl)Cl)Cl,0.012287,0.0004368725355889385,0.4,combined-prediction
-CC(Oc1cc(c(cc1Cl)Cl)n1nc(oc1=O)C(C)(C)C)C,0.0124555,0.1026953824737063,0.4074074074074074,combined-prediction
-CNC(=O)Oc1cccc2c1OC(C2)(C)C,0.01394355,0.11577740543838756,0.5,combined-prediction
-N#Cc1c(Cl)c(C#N)c(c(c1Cl)Cl)Cl,0.015043,0.051870479532762394,0.4,combined-prediction
-Fc1ccc(cc1)[Si](c1ccc(cc1)F)(Cn1cncn1)C,0.015853,0.05068240975245326,0.5625,combined-prediction
-CCOP(=S)(Oc1cc(C)nc(n1)C(C)C)OCC,0.016429,0.00967740922944127,0.30434782608695654,combined-prediction
-N#Cc1c(Cl)cccc1Cl,0.0165685,0.0700468589441214,0.4,combined-prediction
-CCOP(=S)(Oc1nc(Cl)c(cc1Cl)Cl)OCC,0.017114,0.01226732331072138,0.6875,combined-prediction
-BrC1COC(C1)(Cn1cncn1)c1ccc(cc1Cl)Cl,0.017185,0.05948653474874811,0.52,combined-prediction
-CCN(C(=O)SCc1ccc(cc1)Cl)CC,0.0180385,0.058932449375049684,0.4375,combined-prediction
-CCCN(C(=O)n1cncc1)CCOc1c(Cl)cc(cc1Cl)Cl,0.019912,0.05048182950992367,0.21212121212121213,combined-prediction
-CCOC(=O)c1cn2nc(cc2nc1C)OP(=S)(OCC)OCC,0.0200875,0.02036221800054178,0.25,combined-prediction
-COP(=S)(SCN1C(=O)c2c(C1=O)cccc2)OC,0.020484,0.03712628100411957,0.35,combined-prediction
-CNC(=O)ON=C(C(=O)N(C)C)SC,0.022348,0.04646395325144057,0.35294117647058826,combined-prediction
-COC(=O)N(c1ccccc1COc1ccn(n1)c1ccc(cc1)Cl)OC,0.023207,0.06976594438403964,0.1935483870967742,combined-prediction
-CON(C(=O)Nc1ccc(c(c1)Cl)Cl)C,0.025091,0.0672942260939406,0.7857142857142857,combined-prediction
-O=C(NC(=O)c1c(F)cccc1F)Nc1ccc(cc1)Cl,0.025428,0.07143486542742777,0.5454545454545454,combined-prediction
-O=C(N(C)C)Nc1ccc(c(c1)Cl)Cl,0.025741,0.08763643148617718,0.75,combined-prediction
-CCOC(=O)C(Oc1ccc(cc1)Oc1cnc2c(n1)ccc(c2)Cl)C,0.0257509,0.03950626192412149,0.7142857142857143,combined-prediction
-N#Cc1sc2=c(sc1C#N)c(=O)c1c(c2=O)cccc1,0.0269975,0.2852041445987922,0.18181818181818182,combined-prediction
-C=CC1(C)OC(=O)N(C1=O)c1cc(Cl)cc(c1)Cl,0.027961,0.11158677941183813,0.3,combined-prediction
-N#CC(c1ccc(c(c1)Oc1ccccc1)F)OC(=O)C1C(C1(C)C)C=C(Cl)Cl,0.028207,0.05123690024925467,0.8333333333333334,combined-prediction
-CCOC(=O)C(Cc1cc(c(cc1Cl)F)n1nc(n(c1=O)C(F)F)C)Cl,0.029113,0.12980258411559265,0.2857142857142857,combined-prediction
-CON(C(=O)Nc1ccc(cc1)Br)C,0.0313005,0.047684287299270586,0.6,combined-prediction
-CN1CN(C)CSC1=S,0.03266,0.042167946307218554,0.16666666666666666,combined-prediction
-ClCC1CN(C(=O)C1Cl)c1cccc(c1)C(F)(F)F,0.033160999999999996,0.10263065010646152,0.30434782608695654,combined-prediction
-CCCCC(c1ccc(cc1)Cl)(Cn1cncn1)C#N,0.034179,0.0674869108014568,0.6363636363636364,combined-prediction
-CCOP(=S)(SCn1c(=O)oc2c1ccc(c2)Cl)OCC,0.0345288,0.013504300746475848,0.34782608695652173,combined-prediction
-CCOCn1c(c2ccc(cc2)Cl)c(c(c1C(F)(F)F)Br)C#N,0.0350825,0.049265129872245496,0.18181818181818182,combined-prediction
-Clc1ccc(c(c1)Cl)C1(OCCO1)Cn1cncn1,0.0379825,0.06090809324704878,0.6818181818181818,combined-prediction
-CC(C(c1cncnc1)(c1ccc(cc1)OC(F)(F)F)O)C,0.038746,0.03303137710863843,0.17647058823529413,combined-prediction
-CC(N(C(=O)SCC(=C(Cl)Cl)Cl)C(C)C)C,0.041029,0.045614294017447106,0.1111111111111111,combined-prediction
-COP(=S)(Oc1ccc(c(c1)C)[N+](=O)[O-])OC,0.0424911,0.015987779908906877,0.6875,combined-prediction
-O=C1OC(C(=O)N1Nc1ccccc1)(C)c1ccc(cc1)Oc1ccccc1,0.04514,0.08164310780666609,0.23076923076923078,combined-prediction
-CN(C(=S)SSC(=S)N(C)C)C,0.04783,0.049794726539942706,0.375,combined-prediction
-CN(C(=O)Oc1nc(nc(c1C)C)N(C)C)C,0.0520385,0.025108819499171757,0.15384615384615385,combined-prediction
-C=CCOC(c1ccc(cc1Cl)Cl)Cn1cncc1,0.053503,0.047373529225078065,0.23076923076923078,combined-prediction
-COCN(c1c(CC)cccc1CC)C(=O)CCl,0.0537505,0.22753631928651386,0.631578947368421,combined-prediction
-CCOc1ccc2c(c1)C(=CC(N2)(C)C)C,0.055221,0.12551867159377741,0.18518518518518517,combined-prediction
-O=C(c1ccc(cc1S(=O)(=O)C)C(F)(F)F)c1cnoc1C1CC1,0.055661,0.06406237055087671,0.4642857142857143,combined-prediction
-OC(=O)COc1ccc(cc1C)Cl,0.0573225,0.06340785116497763,0.5625,combined-prediction
-CCOC(=O)NCCOc1ccc(cc1)Oc1ccccc1,0.0575765,0.09546482946991192,0.2916666666666667,combined-prediction
-N#CC(c1cccc(c1)Oc1ccccc1)OC(=O)C(c1ccc(cc1)Cl)C(C)C,0.059538,0.049693578400892835,0.7083333333333334,combined-prediction
-N#CC(c1cccc(c1)Oc1ccccc1)OC(=O)C1C(C1(C)C)(C)C,0.060099,0.047652187397508775,0.6363636363636364,combined-prediction
-CC(OC(=O)C(c1ccc(cc1)Br)(c1ccc(cc1)Br)O)C,0.0606145,0.067902946408959,0.6,combined-prediction
-Clc1ccccc1c1nnc(nn1)c1ccccc1Cl,0.06152150000000001,0.08185438372515988,0.36363636363636365,combined-prediction
-Clc1cc(ccc1Oc1ccc(c(c1)C(=O)NS(=O)(=O)C)[N+](=O)[O-])C(F)(F)F,0.062678,0.054971451508403164,0.6296296296296297,combined-prediction
-COc1nc(nc(n1)C)NC(=O)NS(=O)(=O)c1ccccc1Cl,0.062889,0.17590886753271506,0.6071428571428571,combined-prediction
-CCCCN(SN(C(=O)Oc1cccc2c1OC(C2)(C)C)C)CCCC,0.065695,0.05112649561130954,0.5161290322580645,combined-prediction
-O=C(NC(=O)c1c(F)cccc1F)Nc1cc(Cl)c(c(c1F)Cl)F,0.06691,0.07147602610581774,0.5454545454545454,combined-prediction
+N#Cc1nn(c(c1S(=O)C(F)(F)F)N)c1c(Cl)cc(cc1Cl)C(F)(F)F,0.00013611,0.015762350891222954,1,combined-prediction
+OC(=O)C(Oc1ccc(cc1)Oc1ncc(cc1Cl)C(F)(F)F)C,0.00027647,0.01865311387590129,1,combined-prediction
+CCOP(=S)(SCSC(C)(C)C)OCC,0.00027736000000000004,0.002373352833945197,1,combined-prediction
+CCSCSP(=S)(OCC)OCC,0.00061449,0.0008644707029265747,1,combined-prediction
+CCOP(=O)(SC(CC)C)SC(CC)C,0.000872805,0.009749816118717997,1,combined-prediction
+CNC(=O)CSP(=S)(OC)OC,0.0010905,0.006103340712979779,1,combined-prediction
+COP(=O)(SC)N,0.0020549,0.3464870355869287,1,combined-prediction
+CSc1ccc(cc1C)OP(=S)(OC)OC,0.00210185,0.004129614821416341,1,combined-prediction
+CCOP(=S)(Oc1ccc2c(c1)oc(=O)c(c2C)Cl)OCC,0.0033631,0.01857156621251969,1,combined-prediction
+CCOP(=S)(Oc1ncn(n1)c1ccccc1)OCC,0.0041492,0.031009256576671446,1,combined-prediction
+COc1sc(=O)n(n1)CSP(=S)(OC)OC,0.00471335,0.009402776191100103,1,combined-prediction
+CCOP(=S)(OCC)SCSP(=S)(OCC)OCC,0.0049418,0.0011428069287224092,1,combined-prediction
+CCOP(=O)(Oc1ccc(c(c1)C)SC)NC(C)C,0.0049447,0.007157941703199688,1,combined-prediction
+CC(Cc1ccc(cc1)C(C)(C)C)CN1CC(C)OC(C1)C,0.0056016,0.09640139064611304,1,combined-prediction
+COP(=S)(Oc1nc(Cl)c(cc1Cl)Cl)OC,0.00620095,0.015857748213750238,1,combined-prediction
+OC(C(Cl)(Cl)Cl)(c1ccc(cc1)Cl)c1ccc(cc1)Cl,0.0067479,0.057139379343644645,1,combined-prediction
+COC(=O)N(C(=O)N1COC2(C(=N1)c1ccc(cc1C2)Cl)C(=O)OC)c1ccc(cc1)OC(F)(F)F,0.0068203,0.04354935663433701,1,combined-prediction
+Clc1ccc(cc1)C(c1ccccc1Cl)(c1cncnc1)O,0.0075484,0.013465577141591243,1,combined-prediction
+COP(=S)(SCn1nnc2c(c1=O)cccc2)OC,0.0076105,0.0391970094961836,1,combined-prediction
+N#CC(c1cccc(c1)Oc1ccccc1)OC(=O)C1C(C1(C)C)C=C(Br)Br,0.00781875,0.13140623695507206,1,combined-prediction
+CCN(c1nc(cc(n1)C)OP(=S)(OC)OC)CC,0.0081878,0.015434756988461895,1,combined-prediction
+CCCCOC(=O)C(Oc1ccc(cc1)Oc1ccc(cn1)C(F)(F)F)C,0.00885585,0.052569774566266,1,combined-prediction
+COP(=O)(OC=C(Cl)Cl)OC,0.0100688,0.01977816403459902,1,combined-prediction
+CCCSP(=O)(SCCC)OCC,0.010069,0.004021939604880425,1,combined-prediction
+O=S1OCC2C(CO1)C1(C(C2(Cl)C(=C1Cl)Cl)(Cl)Cl)Cl,0.012287,0.0003352201088319376,1,combined-prediction
+CC(Oc1cc(c(cc1Cl)Cl)n1nc(oc1=O)C(C)(C)C)C,0.0124555,0.1437412942013925,1,combined-prediction
+CNC(=O)Oc1cccc2c1OC(C2)(C)C,0.01394355,0.1468896662406669,1,combined-prediction
+N#Cc1c(Cl)c(C#N)c(c(c1Cl)Cl)Cl,0.015043,0.029970384078180506,1,combined-prediction
+Fc1ccc(cc1)[Si](c1ccc(cc1)F)(Cn1cncn1)C,0.015853,0.023290039859847237,1,combined-prediction
+CCOP(=S)(Oc1cc(C)nc(n1)C(C)C)OCC,0.016429,0.010610626582861228,1,combined-prediction
+N#Cc1c(Cl)cccc1Cl,0.0165685,0.05195295050605325,1,combined-prediction
+CCOP(=S)(Oc1nc(Cl)c(cc1Cl)Cl)OCC,0.017114,0.007580517777055951,1,combined-prediction
+BrC1COC(C1)(Cn1cncn1)c1ccc(cc1Cl)Cl,0.017185,0.0405369969743105,1,combined-prediction
+CCN(C(=O)SCc1ccc(cc1)Cl)CC,0.0180385,0.021552868257665423,1,combined-prediction
+CCCN(C(=O)n1cncc1)CCOc1c(Cl)cc(cc1Cl)Cl,0.019912,0.04486014172206608,1,combined-prediction
+CCOC(=O)c1cn2nc(cc2nc1C)OP(=S)(OCC)OCC,0.0200875,0.11039533401959316,1,combined-prediction
+COP(=S)(SCN1C(=O)c2c(C1=O)cccc2)OC,0.020484,0.04208439989396213,1,combined-prediction
+CNC(=O)ON=C(C(=O)N(C)C)SC,0.022348,0.10184241192092622,1,combined-prediction
+COC(=O)N(c1ccccc1COc1ccn(n1)c1ccc(cc1)Cl)OC,0.023207,0.07549049844748126,1,combined-prediction
+CON(C(=O)Nc1ccc(c(c1)Cl)Cl)C,0.025091,0.010621445933840493,1,combined-prediction
+O=C(NC(=O)c1c(F)cccc1F)Nc1ccc(cc1)Cl,0.025428,0.07095019903002926,1,combined-prediction
+O=C(N(C)C)Nc1ccc(c(c1)Cl)Cl,0.025741,0.11660342350291407,1,combined-prediction
+CCOC(=O)C(Oc1ccc(cc1)Oc1cnc2c(n1)ccc(c2)Cl)C,0.0257509,0.04930744903742682,1,combined-prediction
+N#Cc1sc2=c(sc1C#N)c(=O)c1c(c2=O)cccc1,0.0269975,0.3303162902044104,1,combined-prediction
+C=CC1(C)OC(=O)N(C1=O)c1cc(Cl)cc(c1)Cl,0.027961,0.22150776844952555,1,combined-prediction
+N#CC(c1ccc(c(c1)Oc1ccccc1)F)OC(=O)C1C(C1(C)C)C=C(Cl)Cl,0.028207,0.057071467518120804,1,combined-prediction
+CCOC(=O)C(Cc1cc(c(cc1Cl)F)n1nc(n(c1=O)C(F)F)C)Cl,0.029113,0.12520773687665182,1,combined-prediction
+CON(C(=O)Nc1ccc(cc1)Br)C,0.0313005,0.0411876126765006,1,combined-prediction
+CN1CN(C)CSC1=S,0.03266,0.05573360891613872,1,combined-prediction
+ClCC1CN(C(=O)C1Cl)c1cccc(c1)C(F)(F)F,0.033160999999999996,0.24260192407415462,1,combined-prediction
+CCCCC(c1ccc(cc1)Cl)(Cn1cncn1)C#N,0.034179,0.11744820700776244,1,combined-prediction
+CCOP(=S)(SCn1c(=O)oc2c1ccc(c2)Cl)OCC,0.0345288,0.013077751595683798,1,combined-prediction
+CCOCn1c(c2ccc(cc2)Cl)c(c(c1C(F)(F)F)Br)C#N,0.0350825,0.06280543413952969,1,combined-prediction
+Clc1ccc(c(c1)Cl)C1(OCCO1)Cn1cncn1,0.0379825,0.07538715747217808,1,combined-prediction
+CC(C(c1cncnc1)(c1ccc(cc1)OC(F)(F)F)O)C,0.038746,0.024837825071449073,1,combined-prediction
+CC(N(C(=O)SCC(=C(Cl)Cl)Cl)C(C)C)C,0.041029,0.04267853086407376,1,combined-prediction
+COP(=S)(Oc1ccc(c(c1)C)[N+](=O)[O-])OC,0.0424911,0.006153936146948404,1,combined-prediction
+O=C1OC(C(=O)N1Nc1ccccc1)(C)c1ccc(cc1)Oc1ccccc1,0.04514,0.12306247222509399,1,combined-prediction
+CN(C(=S)SSC(=S)N(C)C)C,0.04783,0.04409910789058233,1,combined-prediction
+CN(C(=O)Oc1nc(nc(c1C)C)N(C)C)C,0.0520385,0.01890152025125951,1,combined-prediction
+C=CCOC(c1ccc(cc1Cl)Cl)Cn1cncc1,0.053503,0.0451003678131244,1,combined-prediction
+COCN(c1c(CC)cccc1CC)C(=O)CCl,0.0537505,0.45113861171131114,1,combined-prediction
+CCOc1ccc2c(c1)C(=CC(N2)(C)C)C,0.055221,0.1901267608528008,1,combined-prediction
+O=C(c1ccc(cc1S(=O)(=O)C)C(F)(F)F)c1cnoc1C1CC1,0.055661,0.049393732839805575,1,combined-prediction
+OC(=O)COc1ccc(cc1C)Cl,0.0573225,0.08268164171486121,1,combined-prediction
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-OC(=O)COc1nc(F)c(c(c1Cl)N)Cl,1.9605,0.11355586792202625,0.3157894736842105,combined-prediction
-CC(OC(=O)Nc1cccc(c1)Cl)C,2.3402,0.06474733012562413,0.6923076923076923,combined-prediction
-Oc1ccccc1c1ccccc1,3.1197,0.14128212505165622,0.42857142857142855,combined-prediction
+[O-][N+](=O)c1cc(Cl)c(c(c1)Cl)N,0.72459,0.07849715703838446,1,combined-prediction
+COC(=O)c1c(Cl)c(Cl)c(c(c1Cl)Cl)C(=O)OC,0.768162,2.31508328642089,1,combined-prediction
+COC(=O)NS(=O)(=O)c1ccc(cc1)N,0.78179,0.5017832793530008,1,combined-prediction
+OC(=O)c1nc(Cl)c(c(c1Cl)N)Cl,0.8283,0.7302546414419149,1,combined-prediction
+CC(C1(C)N=C(NC1=O)c1nc2ccccc2cc1C(=O)O)C,0.8351195,0.7859650122662322,1,combined-prediction
+COC(=O)Nc1nc2c([nH]1)cccc2,0.8499450000000001,0.07299963113513676,1,combined-prediction
+CC(Oc1cccc(c1)NC(=O)c1ccccc1C(F)(F)F)C,0.907795,0.14629372991334266,1,combined-prediction
+O=C(C1(C)CCCCC1)Nc1ccc(c(c1Cl)Cl)O,0.96626,0.2951163652473346,1,combined-prediction
+ClCCP(=O)(O)O,0.9723550000000001,3.199405933301164,1,combined-prediction
+COc1cccc(c1C)C(=O)NN(C(C)(C)C)C(=O)c1cc(C)cc(c1)C,1.1154,0.2381461389382947,1,combined-prediction
+CCC(c1noc(c1)NC(=O)c1c(OC)cccc1OC)(CC)C,1.5855,0.9957236632511532,1,combined-prediction
+OC(=O)COc1nc(F)c(c(c1Cl)N)Cl,1.9605,0.18412868248798864,1,combined-prediction
+CC(OC(=O)Nc1cccc(c1)Cl)C,2.3402,0.10764097347364567,1,combined-prediction
+Oc1ccccc1c1ccccc1,3.1197,0.5851984931510728,1,combined-prediction
 OC(=O)CNCP(=O)(O)O,5.5597,0.7008374592406027,0.16666666666666666,combined-prediction
diff --git a/data/combined-test-predictions.id b/data/combined-test-predictions.id
index c8a8308..47f21be 100644
--- a/data/combined-test-predictions.id
+++ b/data/combined-test-predictions.id
@@ -1 +1 @@
-56d482c02b72ed77ae000004
+56d58a282b72ed2e4e000004
diff --git a/figure/test-correlation.pdf b/figure/test-correlation.pdf
index 45f61ff..7592acb 100644
--- a/figure/test-correlation.pdf
+++ b/figure/test-correlation.pdf
diff --git a/figure/test-prediction.pdf b/figure/test-prediction.pdf
index 2fd5761..a19b0d3 100644
--- a/figure/test-prediction.pdf
+++ b/figure/test-prediction.pdf
diff --git a/loael.Rmd b/loael.Rmd
index c34f5f6..0951de6 100644
--- a/loael.Rmd
+++ b/loael.Rmd
@@ -182,7 +182,8 @@ algorithm for the prediction of quantitative properties.  First all fingerprint
 features with identical values across all neighbors are removed.  The reamining
 set of features is used as descriptors for creating a local weighted PLS model
 with atom environments as descriptors and model similarities as weights. The
-`plsr` function of the `pls` R package [@pls] is used for this purpose.
+`pls` method from the `caret` R package [@Kuhn08] is used for this purpose.
+
 Finally the local PLS model is applied to predict the activity of the query
 compound.
 
@@ -190,10 +191,14 @@ If PLS modelling or prediction fails, the program resorts to using the weighted
 mean of the neighbors LOAEL values, where the contribution of each neighbor is
 weighted by its similarity to the query compound.
 
+default settings for tuning
+
 ### Applicability domain
 
 Christoph: TODO
 
+Prediction intervals were obtained from the `predict` function.
+
 ### Validation
 
 For the comparison of experimental variability with predictive accuracies we
diff --git a/loael.md b/loael.md
index 6e6db6d..17fb6e3 100644
--- a/loael.md
+++ b/loael.md
@@ -174,7 +174,8 @@ algorithm for the prediction of quantitative properties.  First all fingerprint
 features with identical values across all neighbors are removed.  The reamining
 set of features is used as descriptors for creating a local weighted PLS model
 with atom environments as descriptors and model similarities as weights. The
-`plsr` function of the `pls` R package [@pls] is used for this purpose.
+`pls` method from the `caret` R package [@Kuhn08] is used for this purpose.
+
 Finally the local PLS model is applied to predict the activity of the query
 compound.
 
@@ -186,6 +187,8 @@ weighted by its similarity to the query compound.
 
 Christoph: TODO
 
+Prediction intervals were obtained from the `predict` function.
+
 ### Validation
 
 For the comparison of experimental variability with predictive accuracies we
@@ -311,7 +314,7 @@ These results are presented in [@fig:corr] and [@tbl:cv]. Please bear in mind th
 Training data | $r^2$                     | RMSE                    
 --------------|---------------------------|-------------------------
 Experimental | 0.49      | 1.41           
-Combined             | 0.38 | 1.47 
+Combined             | 0.38 | 1.51 
 
 : Comparison of model predictions with experimental variability. {#tbl:common-pred}
 
diff --git a/loael.pdf b/loael.pdf
index e8cc2d2..cec8020 100644
--- a/loael.pdf
+++ b/loael.pdf
diff --git a/references.bibtex b/references.bibtex
index 735a52f..897490f 100644
--- a/references.bibtex
+++ b/references.bibtex
@@ -114,3 +114,9 @@ eprint = {
     url = {https://CRAN.R-project.org/package=pls},
   }
 
+@ARTICLE{Kuhn08,
+    author = {Max Kuhn},
+    title = {Building predictive models in R using the caret package},
+    journal = {J. of Stat. Soft},
+    year = {2008}
+}