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Added a CHANGELOG.md to track all project improvements, bug fixes, and feature additions #92

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merged 4 commits into from
Dec 16, 2024
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Added a CHANGELOG.md to track all project improvements, bug fixes, and feature additions #92

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53fee41
Add CHANGELOG to document past milestone fixes and improvements based…
Arc-Celt Dec 16, 2024
4638c46
Add instructions for pytest, complete CHANGELOG.md
Arc-Celt Dec 16, 2024
71d173e
Update the github pages.
Arc-Celt Dec 16, 2024
a5847ab
Try to re-render GitHub pages.
Arc-Celt Dec 16, 2024
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252 changes: 252 additions & 0 deletions CHANGELOG.md
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19 changes: 15 additions & 4 deletions README.md
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Expand Up @@ -97,10 +97,11 @@ If you prefer a containerized environment, use our pre-built Docker image that i

#### Steps

1. Go to the root of this project in the terminal and then run:
```bash
docker compose up
```
1. **Run the Docker Container**
Go to the root of this project in the terminal and then run:
```bash
docker compose up
```
2. **Run the Analysis (Make Targets)**
- To start fresh (remove previously generated files):
```bash
Expand Down Expand Up @@ -169,6 +170,16 @@ If you prefer not to use `make`, you can manually run each step after setting up

---

## Run the Tests

After ensuring that you are in the project root directory, you can run the tests in the terminal with the following command:
```bash
pytest
```
This will execute all the test scripts located in the `tests/` directory within the Docker container.

---

## Updating Dependencies and Docker Image

1. **Add/Update Dependencies**
Expand Down
2 changes: 1 addition & 1 deletion docs/heart_disease_predictor_report_files/libs/bootstrap/bootstrap.min.css
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35 changes: 18 additions & 17 deletions docs/index.html
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Expand Up @@ -333,7 +333,7 @@ <h3 data-number="4.0.1" class="anchored"><span class="header-section-number">4.0
<div id="fig-numeric-distributions" class="quarto-float quarto-figure quarto-figure-center anchored">
<figure class="quarto-float quarto-float-fig figure">
<div aria-describedby="fig-numeric-distributions-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
<img src="results/figures/raw_feature_distributions.png" class="img-fluid figure-img"
<img src="results/figures/eda_output_raw_feature_distributions.png" class="img-fluid figure-img"
style="width:70.0%">
</div>
<figcaption class="quarto-float-caption-bottom quarto-float-caption quarto-float-fig"
Expand All @@ -348,7 +348,7 @@ <h3 data-number="4.0.1" class="anchored"><span class="header-section-number">4.0
<div id="fig-target-distribution" class="quarto-float quarto-figure quarto-figure-center anchored">
<figure class="quarto-float quarto-float-fig figure">
<div aria-describedby="fig-target-distribution-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
<img src="results/figures/target_variable_distribution.png" class="img-fluid figure-img"
<img src="results/figures/eda_output_target_distribution.png" class="img-fluid figure-img"
style="width:75.0%">
</div>
<figcaption class="quarto-float-caption-bottom quarto-float-caption quarto-float-fig"
Expand All @@ -363,7 +363,7 @@ <h3 data-number="4.0.1" class="anchored"><span class="header-section-number">4.0
<div id="fig-categorical-distributions" class="quarto-float quarto-figure quarto-figure-center anchored">
<figure class="quarto-float quarto-float-fig figure">
<div aria-describedby="fig-categorical-distributions-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
<img src="results/figures/categorical_features_distribution.png" class="img-fluid figure-img"
<img src="results/figures/eda_output_categorical_stacked_barplots.png" class="img-fluid figure-img"
style="width:70.0%">
</div>
<figcaption class="quarto-float-caption-bottom quarto-float-caption quarto-float-fig"
Expand All @@ -378,7 +378,8 @@ <h3 data-number="4.0.1" class="anchored"><span class="header-section-number">4.0
<div id="fig-boxplots-class" class="quarto-float quarto-figure quarto-figure-center anchored">
<figure class="quarto-float quarto-float-fig figure">
<div aria-describedby="fig-boxplots-class-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
<img src="results/figures/raw_boxplots_by_class.png" class="img-fluid figure-img" style="width:75.0%">
<img src="results/figures/eda_output_numeric_boxplots.png" class="img-fluid figure-img"
style="width:75.0%">
</div>
<figcaption class="quarto-float-caption-bottom quarto-float-caption quarto-float-fig"
id="fig-boxplots-class-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
Expand Down Expand Up @@ -429,29 +430,29 @@ <h2 data-number="4.1" class="anchored" data-anchor-id="discussion"><span
<tbody>
<tr class="odd">
<td style="text-align: left;">Dummy</td>
<td style="text-align: left;">0.009 (+/- 0.003)</td>
<td style="text-align: left;">0.005 (+/- 0.003)</td>
<td style="text-align: left;">0.009 (+/- 0.002)</td>
<td style="text-align: left;">0.004 (+/- 0.001)</td>
<td style="text-align: left;">0.543 (+/- 0.007)</td>
<td style="text-align: left;">0.542 (+/- 0.002)</td>
</tr>
<tr class="even">
<td style="text-align: left;">Decision tree</td>
<td style="text-align: left;">0.011 (+/- 0.003)</td>
<td style="text-align: left;">0.003 (+/- 0.004)</td>
<td style="text-align: left;">0.009 (+/- 0.000)</td>
<td style="text-align: left;">0.005 (+/- 0.001)</td>
<td style="text-align: left;">0.713 (+/- 0.048)</td>
<td style="text-align: left;">1.000 (+/- 0.000)</td>
</tr>
<tr class="odd">
<td style="text-align: left;">SVC</td>
<td style="text-align: left;">0.010 (+/- 0.003)</td>
<td style="text-align: left;">0.010 (+/- 0.001)</td>
<td style="text-align: left;">0.005 (+/- 0.002)</td>
<td style="text-align: left;">0.844 (+/- 0.043)</td>
<td style="text-align: left;">0.929 (+/- 0.017)</td>
</tr>
<tr class="even">
<td style="text-align: left;">Logistic Regression</td>
<td style="text-align: left;">0.012 (+/- 0.001)</td>
<td style="text-align: left;">0.005 (+/- 0.002)</td>
<td style="text-align: left;">0.011 (+/- 0.001)</td>
<td style="text-align: left;">0.004 (+/- 0.000)</td>
<td style="text-align: left;">0.849 (+/- 0.027)</td>
<td style="text-align: left;">0.889 (+/- 0.015)</td>
</tr>
Expand Down Expand Up @@ -492,22 +493,22 @@ <h2 data-number="4.1" class="anchored" data-anchor-id="discussion"><span
<tbody>
<tr class="odd">
<td style="text-align: left;">Decision Tree</td>
<td style="text-align: left;">0.012 (+/- 0.001)</td>
<td style="text-align: left;">0.004 (+/- 0.003)</td>
<td style="text-align: left;">0.009 (+/- 0.000)</td>
<td style="text-align: left;">0.005 (+/- 0.000)</td>
<td style="text-align: left;">0.778 (+/- 0.037)</td>
<td style="text-align: left;">0.960 (+/- 0.014)</td>
</tr>
<tr class="even">
<td style="text-align: left;">SVC</td>
<td style="text-align: left;">0.008 (+/- 0.003)</td>
<td style="text-align: left;">0.005 (+/- 0.003)</td>
<td style="text-align: left;">0.009 (+/- 0.001)</td>
<td style="text-align: left;">0.005 (+/- 0.002)</td>
<td style="text-align: left;">0.849 (+/- 0.040)</td>
<td style="text-align: left;">0.875 (+/- 0.007)</td>
</tr>
<tr class="odd">
<td style="text-align: left;">Logistic Regression</td>
<td style="text-align: left;">0.012 (+/- 0.001)</td>
<td style="text-align: left;">0.006 (+/- 0.001)</td>
<td style="text-align: left;">0.010 (+/- 0.003)</td>
<td style="text-align: left;">0.005 (+/- 0.002)</td>
<td style="text-align: left;">0.858 (+/- 0.053)</td>
<td style="text-align: left;">0.881 (+/- 0.009)</td>
</tr>
Expand Down
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8 changes: 4 additions & 4 deletions docs/results/tables/baseline_cv_results.csv
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@@ -1,5 +1,5 @@
,fit_time,score_time,test_score,train_score
Dummy,0.009 (+/- 0.003),0.005 (+/- 0.003),0.543 (+/- 0.007),0.542 (+/- 0.002)
Decision tree,0.011 (+/- 0.003),0.003 (+/- 0.004),0.713 (+/- 0.048),1.000 (+/- 0.000)
SVC,0.010 (+/- 0.003),0.005 (+/- 0.002),0.844 (+/- 0.043),0.929 (+/- 0.017)
Logistic Regression,0.012 (+/- 0.001),0.005 (+/- 0.002),0.849 (+/- 0.027),0.889 (+/- 0.015)
Dummy,0.009 (+/- 0.002),0.004 (+/- 0.001),0.543 (+/- 0.007),0.542 (+/- 0.002)
Decision tree,0.009 (+/- 0.000),0.005 (+/- 0.001),0.713 (+/- 0.048),1.000 (+/- 0.000)
SVC,0.010 (+/- 0.001),0.005 (+/- 0.002),0.844 (+/- 0.043),0.929 (+/- 0.017)
Logistic Regression,0.011 (+/- 0.001),0.004 (+/- 0.000),0.849 (+/- 0.027),0.889 (+/- 0.015)
6 changes: 3 additions & 3 deletions docs/results/tables/best_model_cv_results.csv
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@@ -1,4 +1,4 @@
,fit_time,score_time,test_score,train_score
Decision Tree,0.012 (+/- 0.001),0.004 (+/- 0.003),0.778 (+/- 0.037),0.960 (+/- 0.014)
SVC,0.008 (+/- 0.003),0.005 (+/- 0.003),0.849 (+/- 0.040),0.875 (+/- 0.007)
Logistic Regression,0.012 (+/- 0.001),0.006 (+/- 0.001),0.858 (+/- 0.053),0.881 (+/- 0.009)
Decision Tree,0.009 (+/- 0.000),0.005 (+/- 0.000),0.778 (+/- 0.037),0.960 (+/- 0.014)
SVC,0.009 (+/- 0.001),0.005 (+/- 0.002),0.849 (+/- 0.040),0.875 (+/- 0.007)
Logistic Regression,0.010 (+/- 0.003),0.005 (+/- 0.002),0.858 (+/- 0.053),0.881 (+/- 0.009)
50 changes: 25 additions & 25 deletions docs/results/tables/coefficient_df.csv
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@@ -1,26 +1,26 @@
,Feature,Coefficient
0,pipeline-1__ca,0.6746530980012033
1,onehotencoder__cp_4.0,0.6147850844622246
2,pipeline-2__thal_7.0,0.4500905306460702
3,standardscaler__oldpeak,0.4003883492123933
4,onehotencoder__exang_1.0,0.3237249830451551
5,onehotencoder__sex_1.0,0.29767725022535363
6,onehotencoder__slope_2.0,0.2755653019142275
7,standardscaler__trestbps,0.2533412125898724
8,onehotencoder__restecg_2.0,0.16872434784013016
9,onehotencoder__fbs_0.0,0.16101949734866505
10,standardscaler__age,0.02746164282563207
11,standardscaler__chol,0.014375789622327655
12,pipeline-2__thal_6.0,0.006372765391929292
13,onehotencoder__restecg_1.0,-0.007912214031971503
14,onehotencoder__cp_2.0,-0.05575603705702003
15,onehotencoder__slope_3.0,-0.12403495298838915
16,onehotencoder__slope_1.0,-0.15156029269537658
17,onehotencoder__restecg_0.0,-0.16084207757769697
18,onehotencoder__fbs_1.0,-0.16104944111820324
19,onehotencoder__cp_3.0,-0.24539930660403034
20,onehotencoder__sex_0.0,-0.2977071939948918
21,onehotencoder__cp_1.0,-0.31365968457071247
22,onehotencoder__exang_0.0,-0.32375492681469337
23,standardscaler__thalach,-0.40685822469471455
24,pipeline-2__thal_3.0,-0.45649323980753764
0,pipeline-1__ca,0.6746530980013775
1,onehotencoder__cp_4.0,0.6147850844628998
2,pipeline-2__thal_7.0,0.4500905306465596
3,standardscaler__oldpeak,0.4003883492107997
4,onehotencoder__exang_1.0,0.3237249830457789
5,onehotencoder__sex_1.0,0.2976772502272853
6,onehotencoder__slope_2.0,0.27556530191368384
7,standardscaler__trestbps,0.25334121258987014
8,onehotencoder__restecg_2.0,0.16872434784097426
9,onehotencoder__fbs_0.0,0.16101949734960588
10,standardscaler__age,0.027461642823905834
11,standardscaler__chol,0.014375789622254736
12,pipeline-2__thal_6.0,0.006372765392193168
13,onehotencoder__restecg_1.0,-0.007912214030664453
14,onehotencoder__cp_2.0,-0.05575603705710552
15,onehotencoder__slope_3.0,-0.12403495298677863
16,onehotencoder__slope_1.0,-0.1515602926951144
17,onehotencoder__restecg_0.0,-0.16084207757851895
18,onehotencoder__fbs_1.0,-0.16104944111781513
19,onehotencoder__cp_3.0,-0.2453993066042668
20,onehotencoder__sex_0.0,-0.29770719399549445
21,onehotencoder__cp_1.0,-0.3136596845697368
22,onehotencoder__exang_0.0,-0.3237549268139881
23,standardscaler__thalach,-0.40685822469452637
24,pipeline-2__thal_3.0,-0.456493239806962
9 changes: 9 additions & 0 deletions docs/results/tables/eda_output_summary_stats.csv
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@@ -0,0 +1,9 @@
,age,sex,cp,trestbps,chol,fbs,restecg,thalach,exang,oldpeak,slope,ca,thal,num
count,212.0,212.0,212.0,212.0,212.0,212.0,212.0,212.0,212.0,212.0,212.0,212.0,212.0,212.0
mean,54.570754716981135,0.6933962264150944,3.1650943396226414,130.8490566037736,246.9009433962264,0.1509433962264151,1.0518867924528301,149.78301886792454,0.33490566037735847,1.0330188679245282,1.6132075471698113,0.6273584905660378,4.721698113207547,0.45754716981132076
std,8.992345001278341,0.46217472084951555,0.9957770980357741,18.63762308789533,51.636485494046504,0.3588410209234944,0.9938894950423512,22.663206800936447,0.4730745365417657,1.1297126001262536,0.6168372889832545,0.8964419419212969,1.9307688087372425,0.49937365759235375
min,29.0,0.0,1.0,94.0,126.0,0.0,0.0,71.0,0.0,0.0,1.0,0.0,3.0,0.0
25%,48.0,0.0,3.0,120.0,207.75,0.0,0.0,133.75,0.0,0.0,1.0,0.0,3.0,0.0
50%,55.5,1.0,3.5,130.0,245.0,0.0,2.0,153.5,0.0,0.8,2.0,0.0,3.0,0.0
75%,60.25,1.0,4.0,140.0,276.25,0.0,2.0,165.25,1.0,1.6,2.0,1.0,7.0,1.0
max,77.0,1.0,4.0,200.0,564.0,1.0,2.0,202.0,1.0,4.4,3.0,3.0,7.0,1.0