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| import streamlit as st | |
| import os | |
| ROOT_FIG_DIR = f'{os.getcwd()}/figures/' | |
| def get_product_dev_page_layout(): | |
| # row6_1, row6_2, = st.columns((1,1)) | |
| row6_1, row6_2,row6_3 = st.tabs(["Evaluation Metrics", "Performance Evaluation", "Issues and Limitations"]) | |
| with row6_1: | |
| # st.write("**Performance Metrics**") | |
| st.subheader('Performance Metrics') | |
| st.write('Following metrics are used for evaluation:') | |
| st.image(f'{ROOT_FIG_DIR}/evaluation_template.png') | |
| list_test = """<ul> | |
| <li><strong>Accuracy: </strong>it is a ratio of correctly predicted observation to the total observations..</li> | |
| </ul>""" | |
| st.markdown(list_test, unsafe_allow_html=True) | |
| # st.latex(r''' Accuracy=\frac{TP + TN}{TP+TN+FP+FN}''') | |
| list_test = """<ul> | |
| <li><strong>Precision: </strong>It is the ratio of correctly predicted positive observations to the total predicted positive observations</li> | |
| </ul>""" | |
| st.markdown(list_test, unsafe_allow_html=True) | |
| # st.latex(r''' Precision=\frac{TP}{TP+FP}''') | |
| list_test = """<ul> | |
| <li><strong>Recall: </strong>It is the ratio of correctly predicted positive observations to the all observations in actual class.</li> | |
| </ul>""" | |
| st.markdown(list_test, unsafe_allow_html=True) | |
| # st.latex(r''' Recall=\frac{TP}{TP+FN}''') | |
| # with st.expander('Test Set Confusion Matrix'): | |
| # # st.caption('Test Set Results:') | |
| # st.image('./figures/test_confmat_20210404.png') | |
| with row6_2: | |
| # st.write("**Prediction Samples**") | |
| # with st.expander('Test Set Confusion Matrix'): | |
| # # st.caption('Test Set Results:') | |
| st.subheader('Test Set Confusion Matrix') | |
| st.image(f'{ROOT_FIG_DIR}/test_confmat_20210404.png') | |
| # st.subheader('Prediction Samples') | |
| # st.caption('Correctly Classified sample predictions:') | |
| # st.image(f'{ROOT_FIG_DIR}/pred_stats.png') | |
| # st.caption('Miss Classified sample predictions:') | |
| # st.image(f'{ROOT_FIG_DIR}/pred_stats.png') | |
| # st.subheader("Class-wise Prediction Distributions") | |
| # st.image(f'{ROOT_FIG_DIR}/training_prob_stats.png') | |
| with row6_3: | |
| st.write("Weencountered classimbalance issue and here is the miclassified samples...") | |
| st.caption('Miss Classified CNV Samples:') | |
| st.image(f'{ROOT_FIG_DIR}/cnv_missclass.png') | |
| st.caption('Miss Classified NORMAL Samples:') | |
| st.image(f'{ROOT_FIG_DIR}/normal_missclass.png') | |