haizad/ames-housing-random-forest-predictor
Model description
This is a random forest regression model trained on ames housing dataset from OpenML.
Intended uses & limitations
This model is not ready to be used in production.
Training Procedure
[More Information Needed]
Hyperparameters
<details> <summary> Click to expand </summary>
</details>
Model Plot
<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable_label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleablelabel-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleablelabel-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleablelabel-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleablecontent {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleablecontent pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleablecontrol:checked~div.sk-toggleablecontent {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleablecontrol:checked~label.sk-toggleablelabel-arrow:before {content: "▾";}#sk-container-id-1 div.sk-estimator input.sk-toggleablecontrol:checked~label.sk-toggleablelabel {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleablecontrol:checked~label.sk-toggleablelabel {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleablelabel {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-1" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[('columntransformer',ColumnTransformer(transformers=[('simpleimputer',SimpleImputer(addindicator=True),<sklearn.compose.columntransformer.makecolumnselector object at 0x000001EF7028B6D0>),('ordinalencoder',OrdinalEncoder(encodedmissingvalue=-2,handleunknown='useencodedvalue',unknownvalue=-1),<sklearn.compose.columntransformer.makecolumnselector object at 0x000001EF252211B0>)])),('randomforestregressor',RandomForestRegressor(randomstate=42))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleablecontrol sk-hidden--visually" id="sk-estimator-id-1" type="checkbox" ><label for="sk-estimator-id-1" class="sk-toggleablelabel sk-toggleablelabel-arrow">Pipeline</label><div class="sk-toggleablecontent"><pre>Pipeline(steps=[('columntransformer',ColumnTransformer(transformers=[('simpleimputer',SimpleImputer(addindicator=True),<sklearn.compose.columntransformer.makecolumnselector object at 0x000001EF7028B6D0>),('ordinalencoder',OrdinalEncoder(encodedmissingvalue=-2,handleunknown='useencodedvalue',unknownvalue=-1),<sklearn.compose.columntransformer.makecolumnselector object at 0x000001EF252211B0>)])),('randomforestregressor',RandomForestRegressor(randomstate=42))])</pre></div></div></div><div class="sk-serial"><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleablecontrol sk-hidden--visually" id="sk-estimator-id-2" type="checkbox" ><label for="sk-estimator-id-2" class="sk-toggleablelabel sk-toggleablelabel-arrow">columntransformer: ColumnTransformer</label><div class="sk-toggleablecontent"><pre>ColumnTransformer(transformers=[('simpleimputer',SimpleImputer(addindicator=True),<sklearn.compose.columntransformer.makecolumnselector object at 0x000001EF7028B6D0>),('ordinalencoder',OrdinalEncoder(encodedmissingvalue=-2,handleunknown='useencodedvalue',unknownvalue=-1),<sklearn.compose.columntransformer.makecolumnselector object at 0x000001EF252211B0>)])</pre></div></div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable_control sk-hidden--visually" id="sk-estimator-id-3" type="checkbox" ><label for="sk-estimator-id-3" class="sk-toggleablelabel sk-toggleablelabel-arrow">simpleimputer</label><div class="sk-toggleablecontent"><pre><sklearn.compose.columntransformer.makecolumnselector object at 0x000001EF7028B6D0></pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleablecontrol sk-hidden--visually" id="sk-estimator-id-4" type="checkbox" ><label for="sk-estimator-id-4" class="sk-toggleablelabel sk-toggleablelabel-arrow">SimpleImputer</label><div class="sk-toggleablecontent"><pre>SimpleImputer(addindicator=True)</pre></div></div></div></div></div></div><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable_control sk-hidden--visually" id="sk-estimator-id-5" type="checkbox" ><label for="sk-estimator-id-5" class="sk-toggleablelabel sk-toggleablelabel-arrow">ordinalencoder</label><div class="sk-toggleablecontent"><pre><sklearn.compose.columntransformer.makecolumnselector object at 0x000001EF252211B0></pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleablecontrol sk-hidden--visually" id="sk-estimator-id-6" type="checkbox" ><label for="sk-estimator-id-6" class="sk-toggleablelabel sk-toggleablelabel-arrow">OrdinalEncoder</label><div class="sk-toggleablecontent"><pre>OrdinalEncoder(encodedmissingvalue=-2, handleunknown='useencodedvalue',unknownvalue=-1)</pre></div></div></div></div></div></div></div></div><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleablecontrol sk-hidden--visually" id="sk-estimator-id-7" type="checkbox" ><label for="sk-estimator-id-7" class="sk-toggleablelabel sk-toggleablelabel-arrow">RandomForestRegressor</label><div class="sk-toggleablecontent"><pre>RandomForestRegressor(randomstate=42)</pre></div></div></div></div></div></div></div>
Evaluation Results
How to Get Started with the Model
Use the following code to get started:
import joblib
from skops.hub_utils import download
import json
import pandas as pd
download(repo_id="haizad/ames-housing-random-forest-predictor", dst='ames-housing-random-forest-predictor')
pipeline = joblib.load( "ames-housing-random-forest-predictor/model.pkl")
with open("ames-housing-random-forest-predictor/config.json") as f:
config = json.load(f)
pipeline.predict(pd.DataFrame.from_dict(config["sklearn"]["example_input"]))Model Card Authors
This model card is written by following authors:
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[More Information Needed]Intended uses & limitations
This model is not ready to be used in production.