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briangilbert/
MLOOPSZINDI

Name: MLOOPSZINDI
Availability: InStock

sklearn

joblib

tabular-classification

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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)

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Evaluation Results

[More Information Needed]

How to Get Started with the Model

python

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.

briangilbert/MLOOPSZINDI

Model description

Intended uses & limitations

Training Procedure

Hyperparameters

Model Plot

Evaluation Results

How to Get Started with the Model

Model Card Authors

Model Card Contact

Citation

Intended uses & limitations

briangilbert/
MLOOPSZINDI