diff --git a/examples/TmvaBdt.ipynb b/examples/TmvaBdt.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..8e86991e66ab0804604917e25a8054d98d84c866
--- /dev/null
+++ b/examples/TmvaBdt.ipynb
@@ -0,0 +1,112 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pandas as pd\n",
+ "import seaborn as sns\n",
+ "\n",
+ "from nnfwtbn import Variable, Process, Cut, hist, McStack, DataStack, Stack, TmvaBdt\n",
+ "from nnfwtbn import toydata"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df = toydata.get()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Evaluation of TMVA BDT\n",
+ "The file `tmva_bdt.xml` contains a sample BDT trained on the toy dataset. The input variables are\n",
+ " - $\\eta^{j_1}$,\n",
+ " - $\\eta^{j_2}$,\n",
+ " - $\\tau\\;\\mathrm{centrality}$ and\n",
+ " - $\\ell\\;\\mathrm{centrality}$.\n",
+ " \n",
+ "The BDT was trained with regular TMVA in ROOT. The weights stored in the XML file can be read by `nnfwtbn.TmvaBdt` directly."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "bdt = TmvaBdt(\"tmva_bdt.xml\")\n",
+ "df['bdt_prediction'] = bdt.predict(df)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Plotting"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "p_ztt = Process(r\"$Z\\rightarrow\\tau\\tau$\", range=(0, 0))\n",
+ "p_sig = Process(r\"Signal\", range=(1, 1))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "colors = [\"windows blue\", \"amber\", \"greyish\", \"faded green\", \"dusty purple\"]\n",
+ "colors = sns.xkcd_palette(colors)\n",
+ "s_ztt = McStack(p_ztt, color=colors[0], histtype='step')\n",
+ "s_sig = McStack(p_sig, color=colors[1], histtype='step')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "v_bdt = Variable(\"BDT Score\", \"bdt_prediction\")\n",
+ "hist(df, v_bdt, 22, [s_ztt, s_sig], range=(-1.1, 1.1), \n",
+ " weight=\"weight\", numerator=None)\n",
+ "None"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.5"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/tmva_bdt.xml b/examples/tmva_bdt.xml
new file mode 100644
index 0000000000000000000000000000000000000000..19f5ef322eb65758198b27c73dbde2c0ca2d4d3b
--- /dev/null
+++ b/examples/tmva_bdt.xml
@@ -0,0 +1,897 @@
+<?xml version="1.0"?>
+<MethodSetup Method="BDT::BDT">
+ <GeneralInfo>
+ <Info name="TMVA Release" value="4.2.1 [262657]"/>
+ <Info name="ROOT Release" value="6.18/04 [397828]"/>
+ <Info name="Creator" value="Frank"/>
+ <Info name="Date" value="Fri Nov 22 13:24:52 2019"/>
+ <Info name="Host" value="Linux frank-uni 4.15.0-70-generic #79~16.04.1-Ubuntu SMP Tue Nov 12 14:01:10 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux"/>
+ <Info name="Dir" value="/home/frank/repositories/nnfwtbn"/>
+ <Info name="Training events" value="5000"/>
+ <Info name="TrainingTime" value="8.32540989e-02"/>
+ <Info name="AnalysisType" value="Classification"/>
+ </GeneralInfo>
+ <Options>
+ <Option name="V" modified="No">False</Option>
+ <Option name="VerbosityLevel" modified="No">Default</Option>
+ <Option name="VarTransform" modified="No">None</Option>
+ <Option name="H" modified="No">False</Option>
+ <Option name="CreateMVAPdfs" modified="No">False</Option>
+ <Option name="IgnoreNegWeightsInTraining" modified="No">False</Option>
+ <Option name="NTrees" modified="Yes">50</Option>
+ <Option name="MaxDepth" modified="No">3</Option>
+ <Option name="MinNodeSize" modified="No">5%</Option>
+ <Option name="nCuts" modified="No">20</Option>
+ <Option name="BoostType" modified="No">AdaBoost</Option>
+ <Option name="AdaBoostR2Loss" modified="No">quadratic</Option>
+ <Option name="UseBaggedBoost" modified="No">False</Option>
+ <Option name="Shrinkage" modified="No">1.000000e+00</Option>
+ <Option name="AdaBoostBeta" modified="No">5.000000e-01</Option>
+ <Option name="UseRandomisedTrees" modified="No">False</Option>
+ <Option name="UseNvars" modified="No">2</Option>
+ <Option name="UsePoissonNvars" modified="No">True</Option>
+ <Option name="BaggedSampleFraction" modified="No">6.000000e-01</Option>
+ <Option name="UseYesNoLeaf" modified="No">True</Option>
+ <Option name="NegWeightTreatment" modified="No">inverseboostnegweights</Option>
+ <Option name="Css" modified="No">1.000000e+00</Option>
+ <Option name="Cts_sb" modified="No">1.000000e+00</Option>
+ <Option name="Ctb_ss" modified="No">1.000000e+00</Option>
+ <Option name="Cbb" modified="No">1.000000e+00</Option>
+ <Option name="NodePurityLimit" modified="No">5.000000e-01</Option>
+ <Option name="SeparationType" modified="No">giniindex</Option>
+ <Option name="RegressionLossFunctionBDTG" modified="No">huber</Option>
+ <Option name="HuberQuantile" modified="No">7.000000e-01</Option>
+ <Option name="DoBoostMonitor" modified="No">False</Option>
+ <Option name="UseFisherCuts" modified="No">False</Option>
+ <Option name="MinLinCorrForFisher" modified="No">8.000000e-01</Option>
+ <Option name="UseExclusiveVars" modified="No">False</Option>
+ <Option name="DoPreselection" modified="No">False</Option>
+ <Option name="SigToBkgFraction" modified="No">1.000000e+00</Option>
+ <Option name="PruneMethod" modified="No">nopruning</Option>
+ <Option name="PruneStrength" modified="No">0.000000e+00</Option>
+ <Option name="PruningValFraction" modified="No">5.000000e-01</Option>
+ <Option name="SkipNormalization" modified="No">False</Option>
+ <Option name="nEventsMin" modified="No">0</Option>
+ <Option name="UseBaggedGrad" modified="No">False</Option>
+ <Option name="GradBaggingFraction" modified="No">6.000000e-01</Option>
+ <Option name="UseNTrainEvents" modified="No">0</Option>
+ <Option name="NNodesMax" modified="No">0</Option>
+ </Options>
+ <Variables NVar="4">
+ <Variable VarIndex="0" Expression="jet_1_eta" Label="jet_1_eta" Title="jet_1_eta" Unit="" Internal="jet_1_eta" Type="F" Min="-5.72895813e+00" Max="5.73295832e+00"/>
+ <Variable VarIndex="1" Expression="jet_2_eta" Label="jet_2_eta" Title="jet_2_eta" Unit="" Internal="jet_2_eta" Type="F" Min="-5.57531881e+00" Max="5.54892635e+00"/>
+ <Variable VarIndex="2" Expression="lep_centrality" Label="lep_centrality" Title="lep_centrality" Unit="" Internal="lep_centrality" Type="F" Min="0.00000000e+00" Max="1.00000000e+00"/>
+ <Variable VarIndex="3" Expression="tau_centrality" Label="tau_centrality" Title="tau_centrality" Unit="" Internal="tau_centrality" Type="F" Min="0.00000000e+00" Max="1.00000000e+00"/>
+ </Variables>
+ <Spectators NSpec="0"/>
+ <Classes NClass="2">
+ <Class Name="Signal" Index="0"/>
+ <Class Name="Background" Index="1"/>
+ </Classes>
+ <Transformations NTransformations="0"/>
+ <MVAPdfs/>
+ <Weights NTrees="50" AnalysisType="0">
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