metadata
library_name: sklearn
tags:
- sklearn
- tabular-classification
Model description
This is a Logistic Regression model trained on iris dataset. This model could be used to predict type of iris flower, given certain dimensions. This model is very basic and should only be used as an example of how to use Highwind.
Intended uses & limitations
This model is made for the purposes of showing how to use Highwind only.
Training Procedure
[More Information Needed]
Hyperparameters
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Hyperparameter | Value |
---|---|
C | 1 |
class_weight | |
dual | False |
fit_intercept | True |
intercept_scaling | 1 |
l1_ratio | |
max_iter | 100 |
multi_class | auto |
n_jobs | |
penalty | l2 |
random_state | 42 |
solver | lbfgs |
tol | 0.0001 |
verbose | 0 |
warm_start | False |
Model Plot
LogisticRegression(C=1, random_state=42)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
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LogisticRegression(C=1, random_state=42)
Evaluation Results
[More Information Needed]
How to Get Started with the Model
import joblib
from huggingface_hub import hf_hub_download
# Feature scaler
hf_hub_download("MelioAI/iris-classifier", "scaler.joblib")
scaler = joblib.load("scaler.joblib")
# Classifier model
hf_hub_download("MelioAI/iris-classifier", "model.joblib")
model = joblib.load("model.joblib")
Model Card Authors
MelioAI, ruanmelio
Model Card Contact
You can contact the model card authors through following channels: [More Information Needed]
Citation
Below you can find information related to citation.
BibTeX:
[More Information Needed]
Intended uses & limitations
This model is made for the purposes of showing how to use Highwind only.