
# Model description

[More Information Needed]

## Intended uses & limitations

[More Information Needed]

## Training Procedure

### Hyperparameters

The model is trained with below hyperparameters.

<details>
<summary> Click to expand </summary>

| Hyperparameter           | Value   |
|--------------------------|---------|
| ccp_alpha                | 0.0     |
| class_weight             |         |
| criterion                | gini    |
| max_depth                |         |
| max_features             |         |
| max_leaf_nodes           |         |
| min_impurity_decrease    | 0.0     |
| min_impurity_split       |         |
| min_samples_leaf         | 1       |
| min_samples_split        | 2       |
| min_weight_fraction_leaf | 0.0     |
| random_state             |         |
| splitter                 | best    |

</details>

### Model Plot

The model plot is below.

<style>div.sk-top-container {color: black;background-color: white;}div.sk-toggleable {background-color: white;}label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.2em 0.3em;box-sizing: border-box;text-align: center;}div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}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;}div.sk-estimator {font-family: monospace;background-color: #f0f8ff;margin: 0.25em 0.25em;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;}div.sk-estimator:hover {background-color: #d4ebff;}div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;}div.sk-item {z-index: 1;}div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;}div.sk-parallel-item {display: flex;flex-direction: column;position: relative;background-color: white;}div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}div.sk-parallel-item:only-child::after {width: 0;}div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0.2em;box-sizing: border-box;padding-bottom: 0.1em;background-color: white;position: relative;}div.sk-label label {font-family: monospace;font-weight: bold;background-color: white;display: inline-block;line-height: 1.2em;}div.sk-label-container {position: relative;z-index: 2;text-align: center;}div.sk-container {display: inline-block;position: relative;}</style><div class="sk-top-container"><div class="sk-container"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="12a6e028-23d4-4552-93d7-bca81eacd271" type="checkbox" checked><label class="sk-toggleable__label" for="12a6e028-23d4-4552-93d7-bca81eacd271">DecisionTreeClassifier</label><div class="sk-toggleable__content"><pre>DecisionTreeClassifier()</pre></div></div></div></div></div>

## Evaluation Results

You can find the details about evaluation process and the evaluation results.

| Metric   |    Value |
|----------|----------|
| accuracy | 0.935673 |
| f1 score | 0.935673 |

# How to Get Started with the Model

[More Information Needed]

# Model Card Authors

This model card is written by following authors:

[More Information Needed]

# 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]
```

# citation_bibtex

bibtex
@inproceedings{...,year={2020}}

# get_started_code

import pickle 
with open(dtc_pkl_filename, 'rb') as file: 
    clf = pickle.load(file)

# model_card_authors

skops_user

# limitations

This model is not ready to be used in production.

# model_description

This is a DecisionTreeClassifier model trained on breast cancer dataset.

# eval_method

The model is evaluated using test split, on accuracy and F1 score with macro average.

# confusion_matrix

![confusion_matrix](confusion_matrix.png)

{"license": "mit", "library_name": "sklearn", "tags": ["sklearn", "skops", "tabular-classification"], "model_format": "pickle", "model_file": "example.pkl", "widget": {"structuredData": {"area error": [30.29, 96.05, 48.31], "compactness error": [0.01911, 0.01652, 0.01484], "concave points error": [0.01037, 0.0137, 0.01093], "concavity error": [0.02701, 0.02269, 0.02813], "fractal dimension error": [0.003586, 0.001698, 0.002461], "mean area": [481.9, 1130.0, 748.9], "mean compactness": [0.1058, 0.1029, 0.1223], "mean concave points": [0.03821, 0.07951, 0.08087], "mean concavity": [0.08005, 0.108, 0.1466], "mean fractal dimension": [0.06373, 0.05461, 0.05796], "mean perimeter": [81.09, 123.6, 101.7], "mean radius": [12.47, 18.94, 15.46], "mean smoothness": [0.09965, 0.09009, 0.1092], "mean symmetry": [0.1925, 0.1582, 0.1931], "mean texture": [18.6, 21.31, 19.48], "perimeter error": [2.497, 5.486, 3.094], "radius error": [0.3961, 0.7888, 0.4743], "smoothness error": [0.006953, 0.004444, 0.00624], "symmetry error": [0.01782, 0.01386, 0.01397], "texture error": [1.044, 0.7975, 0.7859], "worst area": [677.9, 1866.0, 1156.0], "worst compactness": [0.2378, 0.2336, 0.2394], "worst concave points": [0.1015, 0.1789, 0.1514], "worst concavity": [0.2671, 0.2687, 0.3791], "worst fractal dimension": [0.0875, 0.06589, 0.08019], "worst perimeter": [96.05, 165.9, 124.9], "worst radius": [14.97, 24.86, 19.26], "worst smoothness": [0.1426, 0.1193, 0.1546], "worst symmetry": [0.3014, 0.2551, 0.2837], "worst texture": [24.64, 26.58, 26.0]}}}
sklearn skops tabular-classification license:mit region:us
TAGS
#sklearn #skops #tabular-classification #license-mit #region-us 

Model description
=================


Intended uses & limitations
---------------------------


Training Procedure
------------------


### Hyperparameters


The model is trained with below hyperparameters.



 Click to expand 


### Model Plot


The model plot is below.


URL-top-container {color: black;background-color: white;}URL-toggleable {background-color: white;}URL-toggleable\_\_label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.2em 0.3em;box-sizing: border-box;text-align: center;}URL-toggleable\_\_content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}URL-toggleable\_\_content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}URL-toggleable\_\_control:checked~URL-toggleable\_\_content {max-height: 200px;max-width: 100%;overflow: auto;}URL-estimator URL-toggleable\_\_control:checked~URL-toggleable\_\_label {background-color: #d4ebff;}URL-label URL-toggleable\_\_control:checked~URL-toggleable\_\_label {background-color: #d4ebff;}URL-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;}URL-estimator {font-family: monospace;background-color: #f0f8ff;margin: 0.25em 0.25em;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;}URL-estimator:hover {background-color: #d4ebff;}URL-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}URL-label:hover URL-toggleable\_\_label {background-color: #d4ebff;}URL-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}URL-serial {display: flex;flex-direction: column;align-items: center;background-color: white;}URL-item {z-index: 1;}URL-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;}URL-parallel-item {display: flex;flex-direction: column;position: relative;background-color: white;}URL-parallel-item:first-child::after {align-self: flex-end;width: 50%;}URL-parallel-item:last-child::after {align-self: flex-start;width: 50%;}URL-parallel-item:only-child::after {width: 0;}URL-dashed-wrapped {border: 1px dashed gray;margin: 0.2em;box-sizing: border-box;padding-bottom: 0.1em;background-color: white;position: relative;}URL-label label {font-family: monospace;font-weight: bold;background-color: white;display: inline-block;line-height: 1.2em;}URL-label-container {position: relative;z-index: 2;text-align: center;}URL-container {display: inline-block;position: relative;}DecisionTreeClassifier
```
DecisionTreeClassifier()
```

Evaluation Results
------------------


You can find the details about evaluation process and the evaluation results.



How to Get Started with the Model
=================================


Model Card Authors
==================


This model card is written by following authors:


Model Card Contact
==================


You can contact the model card authors through following channels:


Below you can find information related to citation.


BibTeX:


citation\_bibtex
================


bibtex
@inproceedings{...,year={2020}}


get\_started\_code
==================


import pickle
with open(dtc\_pkl\_filename, 'rb') as file:
clf = URL(file)


model\_card\_authors
====================


skops\_user


limitations
===========


This model is not ready to be used in production.


model\_description
==================


This is a DecisionTreeClassifier model trained on breast cancer dataset.


eval\_method
============


The model is evaluated using test split, on accuracy and F1 score with macro average.


confusion\_matrix
=================


!confusion\_matrix



### Hyperparameters


The model is trained with below hyperparameters.



 Click to expand ### Model Plot


The model plot is below.


URL-top-container {color: black;background-color: white;}URL-toggleable {background-color: white;}URL-toggleable\_\_label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.2em 0.3em;box-sizing: border-box;text-align: center;}URL-toggleable\_\_content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}URL-toggleable\_\_content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}URL-toggleable\_\_control:checked~URL-toggleable\_\_content {max-height: 200px;max-width: 100%;overflow: auto;}URL-estimator URL-toggleable\_\_control:checked~URL-toggleable\_\_label {background-color: #d4ebff;}URL-label URL-toggleable\_\_control:checked~URL-toggleable\_\_label {background-color: #d4ebff;}URL-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;}URL-estimator {font-family: monospace;background-color: #f0f8ff;margin: 0.25em 0.25em;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;}URL-estimator:hover {background-color: #d4ebff;}URL-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}URL-label:hover URL-toggleable\_\_label {background-color: #d4ebff;}URL-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}URL-serial {display: flex;flex-direction: column;align-items: center;background-color: white;}URL-item {z-index: 1;}URL-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;}URL-parallel-item {display: flex;flex-direction: column;position: relative;background-color: white;}URL-parallel-item:first-child::after {align-self: flex-end;width: 50%;}URL-parallel-item:last-child::after {align-self: flex-start;width: 50%;}URL-parallel-item:only-child::after {width: 0;}URL-dashed-wrapped {border: 1px dashed gray;margin: 0.2em;box-sizing: border-box;padding-bottom: 0.1em;background-color: white;position: relative;}URL-label label {font-family: monospace;font-weight: bold;background-color: white;display: inline-block;line-height: 1.2em;}URL-label-container {position: relative;z-index: 2;text-align: center;}URL-container {display: inline-block;position: relative;}DecisionTreeClassifier
```
DecisionTreeClassifier()
```

Evaluation Results
------------------


You can find the details about evaluation process and the evaluation results.



How to Get Started with the Model
=================================


Model Card Authors
==================


This model card is written by following authors:


Model Card Contact
==================


You can contact the model card authors through following channels:


Below you can find information related to citation.


BibTeX:


citation\_bibtex
================


bibtex
@inproceedings{...,year={2020}}


get\_started\_code
==================


import pickle
with open(dtc\_pkl\_filename, 'rb') as file:
clf = URL(file)


model\_card\_authors
====================


skops\_user


limitations
===========


This model is not ready to be used in production.


model\_description
==================


This is a DecisionTreeClassifier model trained on breast cancer dataset.


eval\_method
============


The model is evaluated using test split, on accuracy and F1 score with macro average.


confusion\_matrix
=================


!confusion\_matrix
TAGS
#sklearn #skops #tabular-classification #license-mit #region-us 
 ### Hyperparameters


The model is trained with below hyperparameters.



 Click to expand ### Model Plot


The model plot is below.


URL-top-container {color: black;background-color: white;}URL-toggleable {background-color: white;}URL-toggleable\_\_label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.2em 0.3em;box-sizing: border-box;text-align: center;}URL-toggleable\_\_content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}URL-toggleable\_\_content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}URL-toggleable\_\_control:checked~URL-toggleable\_\_content {max-height: 200px;max-width: 100%;overflow: auto;}URL-estimator URL-toggleable\_\_control:checked~URL-toggleable\_\_label {background-color: #d4ebff;}URL-label URL-toggleable\_\_control:checked~URL-toggleable\_\_label {background-color: #d4ebff;}URL-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;}URL-estimator {font-family: monospace;background-color: #f0f8ff;margin: 0.25em 0.25em;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;}URL-estimator:hover {background-color: #d4ebff;}URL-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}URL-label:hover URL-toggleable\_\_label {background-color: #d4ebff;}URL-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}URL-serial {display: flex;flex-direction: column;align-items: center;background-color: white;}URL-item {z-index: 1;}URL-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;}URL-parallel-item {display: flex;flex-direction: column;position: relative;background-color: white;}URL-parallel-item:first-child::after {align-self: flex-end;width: 50%;}URL-parallel-item:last-child::after {align-self: flex-start;width: 50%;}URL-parallel-item:only-child::after {width: 0;}URL-dashed-wrapped {border: 1px dashed gray;margin: 0.2em;box-sizing: border-box;padding-bottom: 0.1em;background-color: white;position: relative;}URL-label label {font-family: monospace;font-weight: bold;background-color: white;display: inline-block;line-height: 1.2em;}URL-label-container {position: relative;z-index: 2;text-align: center;}URL-container {display: inline-block;position: relative;}DecisionTreeClassifier
```
DecisionTreeClassifier()
```

Evaluation Results
------------------


You can find the details about evaluation process and the evaluation results.



How to Get Started with the Model
=================================


Model Card Authors
==================


This model card is written by following authors:


Model Card Contact
==================


You can contact the model card authors through following channels:


Below you can find information related to citation.


BibTeX:


citation\_bibtex
================


bibtex
@inproceedings{...,year={2020}}


get\_started\_code
==================


import pickle
with open(dtc\_pkl\_filename, 'rb') as file:
clf = URL(file)


model\_card\_authors
====================


skops\_user


limitations
===========


This model is not ready to be used in production.


model\_description
==================


This is a DecisionTreeClassifier model trained on breast cancer dataset.


eval\_method
============


The model is evaluated using test split, on accuracy and F1 score with macro average.


confusion\_matrix
=================


!confusion\_matrix
TAGS
#sklearn #skops #tabular-classification #license-mit #region-us 
### Hyperparameters


The model is trained with below hyperparameters.



 Click to expand### Model Plot


The model plot is below.


URL-top-container {color: black;background-color: white;}URL-toggleable {background-color: white;}URL-toggleable\_\_label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.2em 0.3em;box-sizing: border-box;text-align: center;}URL-toggleable\_\_content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}URL-toggleable\_\_content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}URL-toggleable\_\_control:checked~URL-toggleable\_\_content {max-height: 200px;max-width: 100%;overflow: auto;}URL-estimator URL-toggleable\_\_control:checked~URL-toggleable\_\_label {background-color: #d4ebff;}URL-label URL-toggleable\_\_control:checked~URL-toggleable\_\_label {background-color: #d4ebff;}URL-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;}URL-estimator {font-family: monospace;background-color: #f0f8ff;margin: 0.25em 0.25em;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;}URL-estimator:hover {background-color: #d4ebff;}URL-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}URL-label:hover URL-toggleable\_\_label {background-color: #d4ebff;}URL-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}URL-serial {display: flex;flex-direction: column;align-items: center;background-color: white;}URL-item {z-index: 1;}URL-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;}URL-parallel-item {display: flex;flex-direction: column;position: relative;background-color: white;}URL-parallel-item:first-child::after {align-self: flex-end;width: 50%;}URL-parallel-item:last-child::after {align-self: flex-start;width: 50%;}URL-parallel-item:only-child::after {width: 0;}URL-dashed-wrapped {border: 1px dashed gray;margin: 0.2em;box-sizing: border-box;padding-bottom: 0.1em;background-color: white;position: relative;}URL-label label {font-family: monospace;font-weight: bold;background-color: white;display: inline-block;line-height: 1.2em;}URL-label-container {position: relative;z-index: 2;text-align: center;}URL-container {display: inline-block;position: relative;}DecisionTreeClassifier
```
DecisionTreeClassifier()
```

Evaluation Results
------------------


You can find the details about evaluation process and the evaluation results.



How to Get Started with the Model
=================================


Model Card Authors
==================


This model card is written by following authors:


Model Card Contact
==================


You can contact the model card authors through following channels:


Below you can find information related to citation.


BibTeX:


citation\_bibtex
================


bibtex
@inproceedings{...,year={2020}}


get\_started\_code
==================


import pickle
with open(dtc\_pkl\_filename, 'rb') as file:
clf = URL(file)


model\_card\_authors
====================


skops\_user


limitations
===========


This model is not ready to be used in production.


model\_description
==================


This is a DecisionTreeClassifier model trained on breast cancer dataset.


eval\_method
============


The model is evaluated using test split, on accuracy and F1 score with macro average.


confusion\_matrix
=================


!confusion\_matrix