local_fingerprint_regression with pls (reference)

14 files changed, 783 insertions, 757 deletions

diff --git a/crossvalidation.rb b/crossvalidation.rb
index 1371eb9..eb0c098 100644
--- a/crossvalidation.rb
+++ b/crossvalidation.rb
@@ -5,8 +5,8 @@ file = File.join DATA,ARGV[0]
 csv_file = File.join(DATA,ARGV[0].sub(/.csv/,'-cv.csv'))
 id_file = File.join(DATA,ARGV[0].sub(/.csv/,'-cv.id'))
 dataset = Dataset.from_csv_file file
-model = Model::LazarRegression.create(dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_physchem_regression")
-#model = Model::LazarRegression.create(dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_fingerprint_regression")
+#model = Model::LazarRegression.create(dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_physchem_regression")
+model = Model::LazarRegression.create(dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_fingerprint_regression")
 #model = Model::LazarRegression.create(dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_weighted_average")
 cv = RegressionCrossValidation.create model
 File.open(id_file,"w+"){|f| f.puts cv.id}
diff --git a/data/combined-cv.csv b/data/combined-cv.csv
index 2580c65..b065b56 100644
--- a/data/combined-cv.csv
+++ b/data/combined-cv.csv
@@ -1,611 +1,634 @@
 SMILES,LOAEL_measured_median,LOAEL_predicted,Confidence
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-ClC1=C(Cl)C2(C(C1(Cl)C1C2C2CC1C=C2)(Cl)Cl)Cl,2.7404e-05,0.0001587477178668401,1
-N#Cc1nn(c(c1S(=O)C(F)(F)F)N)c1c(Cl)cc(cc1Cl)C(F)(F)F,0.00013611,0.04039140999987793,1
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-ClC1=C(Cl)C2(C(C1(Cl)C1C2C2CC1C1C2O1)(Cl)Cl)Cl,0.000295345,0.0005384644065654204,1
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diff --git a/data/combined-cv.id b/data/combined-cv.id
index 4544f77..f731528 100644
--- a/data/combined-cv.id
+++ b/data/combined-cv.id
@@ -1 +1 @@
-56d461452b72ed59ca000001
+56d46da02b72ed687e000003
diff --git a/data/combined-test-predictions.csv b/data/combined-test-predictions.csv
index bcaa321..db503b2 100644
--- a/data/combined-test-predictions.csv
+++ b/data/combined-test-predictions.csv
@@ -1,148 +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,0.00013611,0.039022538851494495,1,combined-prediction
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-CCSCSP(=S)(OCC)OCC,0.00061449,0.004623522683397091,1,combined-prediction
-CCOP(=O)(SC(CC)C)SC(CC)C,0.000872805,0.0031944720357688604,1,combined-prediction
-CNC(=O)CSP(=S)(OC)OC,0.0010905,0.0038098395044751563,1,combined-prediction
-COP(=O)(SC)N,0.0020549,0.09818424679489751,1,combined-prediction
-CSc1ccc(cc1C)OP(=S)(OC)OC,0.00210185,0.00988572562602097,1,combined-prediction
-CCOP(=S)(Oc1ccc2c(c1)oc(=O)c(c2C)Cl)OCC,0.0033631,0.02222888639595187,1,combined-prediction
-CCOP(=S)(Oc1ncn(n1)c1ccccc1)OCC,0.0041492,0.016648796015633783,1,combined-prediction
-COc1sc(=O)n(n1)CSP(=S)(OC)OC,0.00471335,0.01321747456225016,1,combined-prediction
-CCOP(=S)(OCC)SCSP(=S)(OCC)OCC,0.0049418,0.015103099200695285,1,combined-prediction
-CCOP(=O)(Oc1ccc(c(c1)C)SC)NC(C)C,0.0049447,0.00592060461106598,1,combined-prediction
-CC(Cc1ccc(cc1)C(C)(C)C)CN1CC(C)OC(C1)C,0.0056016,0.12362254831395794,1,combined-prediction
-COP(=S)(Oc1nc(Cl)c(cc1Cl)Cl)OC,0.00620095,0.010789190380142085,1,combined-prediction
-OC(C(Cl)(Cl)Cl)(c1ccc(cc1)Cl)c1ccc(cc1)Cl,0.0067479,0.04257116270786131,1,combined-prediction
-COC(=O)N(C(=O)N1COC2(C(=N1)c1ccc(cc1C2)Cl)C(=O)OC)c1ccc(cc1)OC(F)(F)F,0.0068203,0.028731721839886464,1,combined-prediction
-Clc1ccc(cc1)C(c1ccccc1Cl)(c1cncnc1)O,0.0075484,0.057931913477062655,1,combined-prediction
-COP(=S)(SCn1nnc2c(c1=O)cccc2)OC,0.0076105,0.022973094599765903,1,combined-prediction
-N#CC(c1cccc(c1)Oc1ccccc1)OC(=O)C1C(C1(C)C)C=C(Br)Br,0.00781875,0.01904109290365828,1,combined-prediction
-CCN(c1nc(cc(n1)C)OP(=S)(OC)OC)CC,0.0081878,0.006469767368123149,1,combined-prediction
-CCCCOC(=O)C(Oc1ccc(cc1)Oc1ccc(cn1)C(F)(F)F)C,0.00885585,0.10230242774331191,1,combined-prediction
-COP(=O)(OC=C(Cl)Cl)OC,0.0100688,0.009448092921794311,1,combined-prediction
-CCCSP(=O)(SCCC)OCC,0.010069,0.004194126927091062,1,combined-prediction
-O=S1OCC2C(CO1)C1(C(C2(Cl)C(=C1Cl)Cl)(Cl)Cl)Cl,0.012287,0.0008008953177590316,1,combined-prediction
-CC(Oc1cc(c(cc1Cl)Cl)n1nc(oc1=O)C(C)(C)C)C,0.0124555,0.06973762406858972,1,combined-prediction
-CNC(=O)Oc1cccc2c1OC(C2)(C)C,0.01394355,0.18360778912736755,1,combined-prediction
-N#Cc1c(Cl)c(C#N)c(c(c1Cl)Cl)Cl,0.015043,0.09015101097920408,1,combined-prediction
-Fc1ccc(cc1)[Si](c1ccc(cc1)F)(Cn1cncn1)C,0.015853,0.05971369163412829,1,combined-prediction
-CCOP(=S)(Oc1cc(C)nc(n1)C(C)C)OCC,0.016429,0.016481950115306176,1,combined-prediction
-N#Cc1c(Cl)cccc1Cl,0.0165685,0.1658161315081919,1,combined-prediction
-CCOP(=S)(Oc1nc(Cl)c(cc1Cl)Cl)OCC,0.017114,0.00978872592951303,1,combined-prediction
-BrC1COC(C1)(Cn1cncn1)c1ccc(cc1Cl)Cl,0.017185,0.03832367626737259,1,combined-prediction
-CCN(C(=O)SCc1ccc(cc1)Cl)CC,0.0180385,0.08348456338735837,1,combined-prediction
-CCCN(C(=O)n1cncc1)CCOc1c(Cl)cc(cc1Cl)Cl,0.019912,0.027040139653104405,1,combined-prediction
-CCOC(=O)c1cn2nc(cc2nc1C)OP(=S)(OCC)OCC,0.0200875,0.0027338392816418176,1,combined-prediction
-COP(=S)(SCN1C(=O)c2c(C1=O)cccc2)OC,0.020484,0.028633323439066778,1,combined-prediction
-CNC(=O)ON=C(C(=O)N(C)C)SC,0.022348,0.044320005108853276,1,combined-prediction
-COC(=O)N(c1ccccc1COc1ccn(n1)c1ccc(cc1)Cl)OC,0.023207,0.03704820705989221,1,combined-prediction
-CON(C(=O)Nc1ccc(c(c1)Cl)Cl)C,0.025091,0.09126100930433,1,combined-prediction
-O=C(NC(=O)c1c(F)cccc1F)Nc1ccc(cc1)Cl,0.025428,0.06621845195538036,1,combined-prediction
-O=C(N(C)C)Nc1ccc(c(c1)Cl)Cl,0.025741,0.10531395667794795,1,combined-prediction
-CCOC(=O)C(Oc1ccc(cc1)Oc1cnc2c(n1)ccc(c2)Cl)C,0.0257509,0.03168944346172917,1,combined-prediction
-N#Cc1sc2=c(sc1C#N)c(=O)c1c(c2=O)cccc1,0.0269975,0.07964244695780903,1,combined-prediction
-C=CC1(C)OC(=O)N(C1=O)c1cc(Cl)cc(c1)Cl,0.027961,0.09142813392134397,1,combined-prediction
-N#CC(c1ccc(c(c1)Oc1ccccc1)F)OC(=O)C1C(C1(C)C)C=C(Cl)Cl,0.028207,0.03698441524216543,1,combined-prediction
-CCOC(=O)C(Cc1cc(c(cc1Cl)F)n1nc(n(c1=O)C(F)F)C)Cl,0.029113,0.07104031118548645,1,combined-prediction
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+CSc1nnc(c(=O)n1N)C(C)(C)C,0.067199,0.013700999999999996,0.11538461538461539,combined-prediction
+O=C(NC(=O)c1c(F)cccc1F)Nc1ccc(c(c1)Cl)OC(C(OC(F)(F)F)F)(F)F,0.06758600000000001,0.0727729584290287,1,combined-prediction
+CCOc1ccc(cc1)C(COCc1cccc(c1)Oc1ccccc1)(C)C,0.068395,0.12969097184986883,1,combined-prediction
+C#CCOS(=O)OC1CCCCC1Oc1ccc(cc1)C(C)(C)C,0.06905,0.07578368745612256,1,combined-prediction
+OC(=O)COc1nc(Cl)c(cc1Cl)Cl,0.07213454999999999,0.03835855467017717,1,combined-prediction
+O=C(N(C)C)Nc1cccc(c1)C(F)(F)F,0.073957,0.06472785712108794,1,combined-prediction
+OC(C(C)(C)C)C(n1cncn1)Oc1ccc(cc1)c1ccccc1,0.074093,0.15306113092024182,1,combined-prediction
+CCNc1nc(NC(C)C)nc(n1)Cl,0.077892,0.03662866389096601,1,combined-prediction
+O=C(C1=C(C)OCCS1)Nc1ccccc1,0.0811745,0.19995933117156434,1,combined-prediction
+CNC(=O)Oc1cc(C)c(c(c1)C)SC,0.0827735,0.02119712521902454,1,combined-prediction
+OC(C(C)(C)C)C(n1ncnc1)Oc1ccc(cc1)Cl,0.084527,0.07787395027854159,1,combined-prediction
+O=C(C(C)(C)C)C(n1ncnc1)Oc1ccc(cc1)Cl,0.085107,0.059994105187728,1,combined-prediction
+CC(NC(=O)N1CC(=O)N(C1=O)c1cc(Cl)cc(c1)Cl)C,0.08783250000000001,0.07101972677280408,1,combined-prediction
+CCC(=O)Nc1ccc(c(c1)Cl)Cl,0.09171,0.1683220443751839,1,combined-prediction
+N#CC(c1ccccc1)(Cn1cncn1)CCc1ccc(cc1)Cl,0.092038,0.04845397355583842,1,combined-prediction
+ClC(=CC1C(C1(C)C)C(=O)OCc1cccc(c1)Oc1ccccc1)Cl,0.095836,0.04676230306141561,1,combined-prediction
+OC(=O)C(Oc1ccc(cc1Cl)Cl)C,0.0967835,0.023553901574432327,1,combined-prediction
+COP(=O)(NC(=O)C)SC,0.1023645,0.019320843216245713,1,combined-prediction
+O=C1N(c2cc(Cl)cc(c2)Cl)C(=O)C2(C1(C)C2)C,0.1108605,0.09149210280557851,1,combined-prediction
+COC(=O)c1c(nc(c(c1CC(C)C)C1=NCCS1)C(F)(F)F)C(F)F,0.11151,0.034031192189321297,1,combined-prediction
+Clc1ccc(cc1)CCC(C(C)(C)C)(Cn1cncn1)O,0.115167,0.050599317477521444,1,combined-prediction
+COC(=O)NC(=S)Nc1ccccc1NC(=S)NC(=O)OC,0.12412500000000001,0.2181570517004251,1,combined-prediction
+CCOc1cc(ccc1[N+](=O)[O-])Oc1ccc(cc1Cl)C(F)(F)F,0.12856,0.07479438797934171,1,combined-prediction
+CCc1ccc(cc1)C(=O)NN(C(C)(C)C)C(=O)c1cc(C)cc(c1)C,0.13674999999999998,0.8492604477853548,1,combined-prediction
+c1scc(n1)c1nc2c([nH]1)cccc2,0.14907,0.07471063996365886,1,combined-prediction
+CC(N1C(=O)c2ccccc2NS1(=O)=O)C,0.14983,0.6680577816178437,1,combined-prediction
+N#CC(c1cccc(c1)Oc1ccccc1)OC(=O)C1C(C1(C)C)C=C(Cl)Cl,0.150135,0.012975994806076651,1,combined-prediction
+Cc1cccc2c1n1cnnc1s2,0.150605,0.3498252591119686,1,combined-prediction
+ClC(SN1C(=O)c2c(C1=O)cccc2)(Cl)Cl,0.15173999999999999,0.24244675308187724,1,combined-prediction
+CCC(Nc1c(cc(cc1[N+](=O)[O-])C(C)(C)C)[N+](=O)[O-])C,0.153385,0.08328649228253959,1,combined-prediction
+Cc1nc(Nc2ccccc2)nc(c1)C1CC1,0.15802,0.21570853112934488,1,combined-prediction
+c1ccc(cc1)Nc1ccccc1,0.16546,0.2677642279225283,1,combined-prediction
+Clc1cc(Cl)c(cc1n1nc(n(c1=O)C(F)F)C)NS(=O)(=O)C,0.17304,0.024481622955652305,1,combined-prediction
+CCCC1COC(O1)(Cn1cncn1)c1ccc(cc1Cl)Cl,0.176786,0.03452095766996186,1,combined-prediction
+C#CCC1=C(C)C(CC1=O)OC(=O)C1C(C1(C)C)C=C(C)C,0.18558899999999998,0.17929424871073593,1,combined-prediction
+COc1nc(nc(n1)C)NC(=O)NS(=O)(=O)c1ccccc1CCC(F)(F)F,0.200175,0.1213890580818667,1,combined-prediction
+CC(=CC1C(C1(C)C)C(=O)OCc1coc(c1)Cc1ccccc1)C,0.2068305,0.1676746217952649,1,combined-prediction
+CCOCN(c1c(C)cccc1CC)C(=O)CCl,0.21666999999999997,0.07094256626109705,1,combined-prediction
+CC(Nc1nc(NC(C)C)nc(n1)Cl)C,0.219845,0.056901323190921005,1,combined-prediction
+CNC(=O)Oc1ccccc1OC(C)C,0.23418,0.047327018168285516,1,combined-prediction
+CCCCCCCCSC(=O)Oc1cc(Cl)nnc1c1ccccc1,0.24081999999999998,0.1566941231767996,1,combined-prediction
+O=C1N(OCC1(C)C)Cc1ccccc1Cl,0.253443,0.07813173315568359,1,combined-prediction
+Cc1ccc(cc1)N(S(=O)(=O)N(C)C)SC(Cl)(Cl)F,0.25917,0.07021034402634173,1,combined-prediction
+CC1N(C(=O)NC2CCCCC2)C(=O)SC1c1ccc(cc1)Cl,0.259436,0.03799064836715854,1,combined-prediction
+CCN(C(=O)C(Oc1cccc2c1cccc2)C)CC,0.271895,0.27352604859901297,1,combined-prediction
+OC(=O)COc1ccc(cc1Cl)Cl,0.2805,0.046980681737664176,1,combined-prediction
+CCOC(=O)CC(C(=O)OCC)SP(=S)(OC)OC,0.292105,0.02787070420230391,1,combined-prediction
+CNC(=O)Oc1cccc2c1cccc2,0.29818,0.10924866433596304,1,combined-prediction
+Clc1ccc(cc1)CN(C(=O)Nc1ccccc1)C1CCCC1,0.31170800000000004,0.07045286029635517,1,combined-prediction
+ClCCOc1ccccc1S(=O)(=O)NC(=O)Nc1nc(C)nc(n1)OC,0.31207450000000003,0.14020939598069498,1,combined-prediction
 CCC(n1c(=O)[nH]c(c(c1=O)Br)C)C,0.31690999999999997,0.2948401415996648,0.25,combined-prediction
-ClC(SN1C(=O)C2C(C1=O)CC=CC2)(Cl)Cl,0.32935499999999995,0.14257378251230177,1,combined-prediction
-CC(=CC1C(C1(C)C)C(=O)OCc1cccc(c1)Oc1ccccc1)C,0.42802,0.08343135544634725,1,combined-prediction
-CC(Oc1ccccn1)COc1ccc(cc1)Oc1ccccc1,0.433615,0.09694437737358237,1,combined-prediction
-N#Cc1c[nH]cc1c1cccc2c1OC(O2)(F)F,0.449265,0.12064410035168348,1,combined-prediction
-Clc1c(Cl)c([N+](=O)[O-])c(c(c1Cl)Cl)Cl,0.47404,0.07884919893678415,1,combined-prediction
-COc1nc(nc(n1)C)NC(=O)NS(=O)(=O)c1ccccc1C(=O)OC,0.48379,0.2799528445986078,1,combined-prediction
-Nc1nc(NC2CC2)nc(n1)N,0.514491,0.05608059754600411,1,combined-prediction
-CCCCOCCOCCOCc1cc2OCOc2cc1CCC,0.51708,0.2592218632933141,1,combined-prediction
-COCC(N(c1c(C)cccc1CC)C(=O)CCl)C,0.52855,0.13140280289407213,1,combined-prediction
-[O-][N+](=O)c1cc(Cl)c(c(c1)Cl)N,0.72459,0.1983616156820635,1,combined-prediction
-COC(=O)c1c(Cl)c(Cl)c(c(c1Cl)Cl)C(=O)OC,0.768162,0.6444380783198541,1,combined-prediction
-COC(=O)NS(=O)(=O)c1ccc(cc1)N,0.78179,0.3915874058471919,1,combined-prediction
-OC(=O)c1nc(Cl)c(c(c1Cl)N)Cl,0.8283,0.6607447731263508,1,combined-prediction
-CC(C1(C)N=C(NC1=O)c1nc2ccccc2cc1C(=O)O)C,0.8351195,0.12844087969884085,1,combined-prediction
-COC(=O)Nc1nc2c([nH]1)cccc2,0.8499450000000001,0.14784204757583647,1,combined-prediction
-CC(Oc1cccc(c1)NC(=O)c1ccccc1C(F)(F)F)C,0.907795,0.10858575592662774,1,combined-prediction
-O=C(C1(C)CCCCC1)Nc1ccc(c(c1Cl)Cl)O,0.96626,0.09941079821123901,1,combined-prediction
-ClCCP(=O)(O)O,0.9723550000000001,2.433436432155647,1,combined-prediction
-COc1cccc(c1C)C(=O)NN(C(C)(C)C)C(=O)c1cc(C)cc(c1)C,1.1154,0.1402859993986547,1,combined-prediction
-CCC(c1noc(c1)NC(=O)c1c(OC)cccc1OC)(CC)C,1.5855,0.4517086261839305,1,combined-prediction
-OC(=O)COc1nc(F)c(c(c1Cl)N)Cl,1.9605,0.375096566193633,1,combined-prediction
-CC(OC(=O)Nc1cccc(c1)Cl)C,2.3402,0.0850988265466987,1,combined-prediction
-Oc1ccccc1c1ccccc1,3.1197,0.3177483474668348,1,combined-prediction
+ClC(SN1C(=O)C2C(C1=O)CC=CC2)(Cl)Cl,0.32935499999999995,0.07976078042600027,1,combined-prediction
+CC(=CC1C(C1(C)C)C(=O)OCc1cccc(c1)Oc1ccccc1)C,0.42802,0.05384554925787951,1,combined-prediction
+CC(Oc1ccccn1)COc1ccc(cc1)Oc1ccccc1,0.433615,0.14205419332591468,1,combined-prediction
+N#Cc1c[nH]cc1c1cccc2c1OC(O2)(F)F,0.449265,0.21012004855094796,1,combined-prediction
+Clc1c(Cl)c([N+](=O)[O-])c(c(c1Cl)Cl)Cl,0.47404,0.061353356149842234,1,combined-prediction
+COc1nc(nc(n1)C)NC(=O)NS(=O)(=O)c1ccccc1C(=O)OC,0.48379,0.09458747661813943,1,combined-prediction
+Nc1nc(NC2CC2)nc(n1)N,0.514491,0.1160911747781518,1,combined-prediction
+CCCCOCCOCCOCc1cc2OCOc2cc1CCC,0.51708,0.3407671414577521,1,combined-prediction
+COCC(N(c1c(C)cccc1CC)C(=O)CCl)C,0.52855,0.10057456723782453,1,combined-prediction
+O=Cc1ccco1,0.62445,0.12487,0.1111111111111111,combined-prediction
+[O-][N+](=O)c1cc(Cl)c(c(c1)Cl)N,0.72459,0.12418355176644183,1,combined-prediction
+COC(=O)c1c(Cl)c(Cl)c(c(c1Cl)Cl)C(=O)OC,0.768162,0.7718941842378951,1,combined-prediction
+COC(=O)NS(=O)(=O)c1ccc(cc1)N,0.78179,0.47721321130047156,1,combined-prediction
+OC(=O)c1nc(Cl)c(c(c1Cl)N)Cl,0.8283,0.6037122433930873,1,combined-prediction
+CC(C1(C)N=C(NC1=O)c1nc2ccccc2cc1C(=O)O)C,0.8351195,0.8106366739911756,1,combined-prediction
+COC(=O)Nc1nc2c([nH]1)cccc2,0.8499450000000001,0.0833355353580093,1,combined-prediction
+CC(Oc1cccc(c1)NC(=O)c1ccccc1C(F)(F)F)C,0.907795,0.10858688334353366,1,combined-prediction
+O=C(C1(C)CCCCC1)Nc1ccc(c(c1Cl)Cl)O,0.96626,0.45051257469048867,1,combined-prediction
+ClCCP(=O)(O)O,0.9723550000000001,2.4009973601180943,1,combined-prediction
+COc1cccc(c1C)C(=O)NN(C(C)(C)C)C(=O)c1cc(C)cc(c1)C,1.1154,0.27892917563036485,1,combined-prediction
+CCC(c1noc(c1)NC(=O)c1c(OC)cccc1OC)(CC)C,1.5855,0.4457808075272036,1,combined-prediction
+OC(=O)COc1nc(F)c(c(c1Cl)N)Cl,1.9605,0.12629032616320499,1,combined-prediction
+CC(OC(=O)Nc1cccc(c1)Cl)C,2.3402,0.12374297824529319,1,combined-prediction
+Oc1ccccc1c1ccccc1,3.1197,0.23249187284217376,1,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 53a9c30..beb87b2 100644
--- a/data/combined-test-predictions.id
+++ b/data/combined-test-predictions.id
@@ -1 +1 @@
-56d468182b72ed5b57000004
+56d470502b72ed6930000006
diff --git a/figure/crossvalidation.pdf b/figure/crossvalidation.pdf
index 92ef43d..03f324c 100644
--- a/figure/crossvalidation.pdf
+++ b/figure/crossvalidation.pdf
diff --git a/figure/dataset-variability.pdf b/figure/dataset-variability.pdf
index 3fca96d..942e345 100644
--- a/figure/dataset-variability.pdf
+++ b/figure/dataset-variability.pdf
diff --git a/figure/functional-groups.pdf b/figure/functional-groups.pdf
index 5fb3cba..a4b02b2 100644
--- a/figure/functional-groups.pdf
+++ b/figure/functional-groups.pdf
diff --git a/figure/test-correlation.pdf b/figure/test-correlation.pdf
index 8363a8b..6e0ed2e 100644
--- a/figure/test-correlation.pdf
+++ b/figure/test-correlation.pdf
diff --git a/figure/test-prediction.pdf b/figure/test-prediction.pdf
index 77200bc..361145d 100644
--- a/figure/test-prediction.pdf
+++ b/figure/test-prediction.pdf
diff --git a/include.rb b/include.rb
index 080f9fe..edc3a64 100644
--- a/include.rb
+++ b/include.rb
@@ -1,4 +1,4 @@
-require_relative '../../lazar/lib/lazar'
+require_relative '../lazar/lib/lazar'
 include OpenTox
 DATA = File.join(File.dirname(__FILE__),"data")
 #$mongo.database.drop
diff --git a/loael.md b/loael.md
index a1707ad..2cb3014 100644
--- a/loael.md
+++ b/loael.md
@@ -311,7 +311,7 @@ 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             | 0.34 | 1.51 
+Combined             | 0.38 | 1.48 
 
 : Comparison of model predictions with experimental variability. {#tbl:common-pred}
 
@@ -325,7 +325,7 @@ All correlations are statistically highly significant with a p-value < 2.2e-16.
 
 Training dataset | $r^2$ | RMSE 
 -----------------|-------|------
-Combined | 0.32  | 1.96 
+Combined | 0.37  | 1.84 
 
 : 10-fold crossvalidation results {#tbl:cv}
 
diff --git a/loael.pdf b/loael.pdf
index 5867b20..8147805 100644
--- a/loael.pdf
+++ b/loael.pdf
diff --git a/test-validation.rb b/test-validation.rb
index 5edd6e6..71dc4b3 100644
--- a/test-validation.rb
+++ b/test-validation.rb
@@ -4,8 +4,8 @@ test = Dataset.from_csv_file(File.join(DATA,"test.csv"))
 
 file = File.join(DATA,ARGV[0])
 dataset = Dataset.from_csv_file file
-model = Model::LazarRegression.create(dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_physchem_regression")
-#model = Model::LazarRegression.create(dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_fingerprint_regression")
+model = Model::LazarRegression.create(dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_fingerprint_regression")
+#model = Model::LazarRegression.create(dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_physchem_regression")
 #model = Model::LazarRegression.create(dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_weighted_average")
 validation = RegressionValidation.create model, dataset, test
 csv_file = file.sub(".csv","-test-predictions.csv")