6f16f0ef58
* Fix various typos * Add override to functions that are overridden gcc gives warnings about functions that are being overridden by not being marked as oveirridden. This fixes it. * Use bst_float consistently Use bst_float for all the variables that involve weight, leaf value, gradient, hessian, gain, loss_chg, predictions, base_margin, feature values. In some cases, when due to additions and so on the value can take a larger value, double is used. This ensures that type conversions are minimal and reduces loss of precision.
108 lines
2.0 KiB
Plaintext
108 lines
2.0 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# XGBoost Model Analysis\n",
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"\n",
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"This notebook can be used to load and analysis model learnt from all xgboost bindings, including distributed training. "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"import sys\n",
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"import os\n",
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"%matplotlib inline "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Please change the ```pkg_path``` and ```model_file``` to be correct path"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"pkg_path = '../../python-package/'\n",
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"model_file = 's3://my-bucket/xgb-demo/model/0002.model'\n",
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"sys.path.insert(0, pkg_path)\n",
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"import xgboost as xgb"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Plot the Feature Importance"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"# plot the first two trees.\n",
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"bst = xgb.Booster(model_file=model_file)\n",
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"xgb.plot_importance(bst)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Plot the First Tree"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"tree_id = 0\n",
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"xgb.to_graphviz(bst, tree_id)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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