Week 10: Discussion

Why ROC is important?

Why ROC is important?

by Al Amin Biswas -
Number of replies: 89

  

In reply to Al Amin Biswas

Re: Why ROC is important?

by MD. Harun-Or-Rashid -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by MD. AL- HABIB ISLAM -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by sakhawt hosen (191-15-2586) -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by sakhawt hosen (191-15-2586) -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Rakibul Islam 191-15-2388 -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Salma Akter 191-15-2387 -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Md.Moshiur Rahman -
#Let's see why ROC is important:
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test.
As the area under an ROC curve is a measure of the usefulness of a test in general,
where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
That is why ROC is important.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Shorove Tajmen -
ROC (receiver operating characteristic curve) is a probability curve. It is used for the measurement of the classification problems at various threshold settings. The ROC curve is produced by calculating and plotting the true positive rate against the false-positive rate for a single classifier at a variety of thresholds.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Md. Muzahidul Islam Khandakar -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Rashiduzzaman Shakil -
A ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters: 1. True Positive Rate and 2. False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Ritu Biswas -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Md. Abir Rahaman -
At various threshold levels, the ROC is used to measure categorization issues. Calculating and displaying the true-positive rate against the false-positive rate for a single classifier at various thresholds yields the ROC curve.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Tuzammal Hossain Masum -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Md Rifat Bhuiyan -
ROC (receiver operating characteristic curve) is a probability curve. It is used for the measurement of the classification problems at various threshold settings. The ROC curve is produced by calculating and plotting the true positive rate against the false-positive rate for a single classifier at a variety of thresholds
In reply to Al Amin Biswas

Re: Why ROC is important?

by Rasel Hider Nobin -
“Receiver Characteristic Operator” (ROC) s a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters: 1. True Positive Rate 2. False Positive Rate. The AUC-ROC curve tells us to visualize how well our machine learning classifier is carrying out. It is one of the most significant evaluation metrics for examining any classification model's performance.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Sayma Islam -
A receiver operating characteristic curve (ROC curve) is a graph that shows how well a classification model performs across all categorization levels. Two parameters are shown on this curve:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Tajul Islam Ayon -
“Receiver Characteristic Operator” (ROC) s a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters: 1. True Positive Rate 2. False Positive Rate. The AUC-ROC curve tells us to visualize how well our machine learning classifier is carrying out. It is one of the most significant evaluation metrics for examining any classification model's performance.
In reply to Al Amin Biswas

Re: Why ROC is important?

by MD.ROBIUL HASAN -
ROC curves are frequently used to show in a graphical way the connection/trade-off between clinical sensitivity and specificity for every possible cut-off for a test or a combination of tests. In addition, the area under the ROC curve gives an idea about the benefit of using the test(s) in question. The areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by MD. Sazzad Hossain Bhuiyan Sakib -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by shoriful islam shakil -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Chaity Mondol -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Md. Zahir Rayhan -
A ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters: 1. True Positive Rate and 2. False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Md Shazzad -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under a ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Al- mamun -
ROC curves are frequently used to show in a graphical way the connection/trade-off between clinical sensitivity and specificity for every possible cut-off for a test or a combination of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Faruq Hossain -
ROC curves are commonly used to depict the relationship/trade-off between clinical sensitivity and specificity for each conceivable cut-off for a test or a set of tests in a graphical format.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Taslima Sathi -
ROC curves are commonly used to depict the relationship/trade-off between clinical sensitivity and specificity for each conceivable cut-off for a test or a set of tests in a graphical format. Furthermore, the area under the ROC curve provides insight into the value of using the test(s) in question.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Shamim Raihan -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Tanvir Hasan (191-15-2463) -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Fazlay Atif Maruf -
The “Receiver Characteristic Operator” (ROC) is a graph that depicts a classification model's performance across all categorization thresholds. Two parameters are plotted on this curve: 1. Rate of True Positives 2. The rate of false positives. The AUC-ROC curve is a visual representation of how effectively our machine learning classifier is performing. It is one of the most important measures for evaluating any classification method.
In reply to Al Amin Biswas

Re: Why ROC is important?

by golam kibria khan -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Sharaf Rad -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Mehedi Hasan -
ROC curves are frequently used to show in a graphical way the connection/trade-off between clinical sensitivity and specificity for every possible cut-off for a test or a combination of tests. In addition the area under the ROC curve gives an idea about the benefit of using the test(s) in question.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Saidul Alam 191-15-2703 -
“Receiver Characteristic Operator” (ROC) s a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters: 1. True Positive Rate 2. False Positive Rate. The AUC-ROC curve tells us to visualize how well our machine learning classifier is carrying out. It is one of the most significant evaluation metrics for examining any classification model's performance.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Khadiza Rimi -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Shakil Khan -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Alimujjaman Bappy -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Sanzida Mukti -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Md Limon Hossen -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests
In reply to Al Amin Biswas

Re: Why ROC is important?

by Soriful Alam Shetu(191-15-2408) -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Abdullah Al Mahmud 241-25-038 -
A receiver operating characteristic curve (ROC curve) is a graph that shows how well a classification model performs across all categorization levels. Two parameters are shown on this curve:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Inam Ullah Khan(191-15-2575) -
ROC curves are frequently used to show in a graphical way the connection/trade-off between clinical sensitivity and specificity for every possible cut-off for a test or a combination of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by ABDUR RAHMAN -
ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:
True Positive Rate. False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Aysha Akter Anjuman -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Swarna Roy191-15-2509 -

An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate

In reply to Al Amin Biswas

Re: Why ROC is important?

by Abdullah All Mukit -
#Let's see why ROC is important:
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test.
As the area under an ROC curve is a measure of the usefulness of a test in general,
where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
That is why ROC is important.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Md. Abid Hasan -
A ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters: 1. True Positive Rate and 2. False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Bonna Akter -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:
True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Riad Shalahin Leon -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests
In reply to Al Amin Biswas

Re: Why ROC is important?

by Israt jahan Shoshe -
A receiver operating characteristic curve (ROC curve) is a graph that shows how well a classification model performs across all categorization levels. Two parameters are shown on this curve:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Anika Tafannum -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Farzana Akter -
A ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters: 1. True Positive Rate and 2. False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Shahida Akter -
A receiver operating characteristic curve (ROC curve) is a graph that shows how well a classification model performs across all categorization levels. Two parameters are shown on this curve:
In reply to Al Amin Biswas

Re: Why ROC is important?

by Mirza Shahriyar Rahman -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Ismatara Nodi -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Md Ali Al Alvy -
The ROC curve is used in clinical biochemistry to select the most suitable cut-off for an experiment. Since the area under a ROC curve is generally a measure of the usefulness of a test, where a larger area means a more useful test, areas under the ROC curve are used to compare the suitability of the test.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Nahid Sharif -
ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Robiul Islam -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Mokhlesur Rahman -

ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.

In reply to Al Amin Biswas

Re: Why ROC is important?

by Sabbir Ahmad -
ROC curves are frequently used to show in a graphical way the connection/trade-off between clinical sensitivity and specificity for every possible cut-off for a test or a combination of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Mahsuba meherunnessa Samia -

ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.

In reply to Al Amin Biswas

Re: Why ROC is important?

by MD ALI AZAM -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Kayes Uddin Fahim -
ROC curves are frequently used to show in a graphical way the connection/trade-off between clinical sensitivity and specificity for every possible cut-off for a test or a combination of tests. In addition, the area under the ROC curve gives an idea about the benefit of using the test(s) in question. The areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Momenunnessa Meem -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Alamin Dhaly -
ROC is a probability curve used for the measurement of the classification problems at various threshold settings. The ROC curve is produced by calculating and plotting the TPR against the FPR for a single classifier at a variety of thresholds.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Inam Ullah Khan(191-15-2575) -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Salma Akter 191-15-2387 -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by MD. Sazzad Hossain Bhuiyan Sakib -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests
In reply to Al Amin Biswas

Re: Why ROC is important?

by Aunik Hasan Mridul -
ROC (receiver operating characteristic curve) is a probability curve. It is used for the measurement of the classification problems at various threshold settings. The ROC curve is produced by calculating and plotting the true positive rate against the false-positive rate for a single classifier at a variety of thresholds.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Abu Sufian -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests
In reply to Al Amin Biswas

Re: Why ROC is important?

by Mustahsin Al Rafi -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by md.ziad hosen -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Md.Jahidul Islam -
ROC (receiver operating characteristic curve) is a probability curve. It is used for the measurement of the classification problems at various threshold settings. The ROC curve is produced by calculating and plotting the true positive rate against the false-positive rate for a single classifier at a variety of thresholds
In reply to Al Amin Biswas

Re: Why ROC is important?

by Sadikuzzaman Shawon -
A ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters: 1. True Positive Rate and 2. False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Progga Parmita Karmokar -
The ROC curve is used in clinical biochemistry to select the most suitable cut-off for an experiment. Since the area under a ROC curve is generally a measure of the usefulness of a test, where a larger area means a more useful test, areas under the ROC curve are used to compare the suitability of the test.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Soriful Alam Shetu(191-15-2408) -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Md.Robiul Hasan Raian -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. As the area under a ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Sabbir Ahmad -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Ahasanul Kobir Opy -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by md.shahin alom -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:
In reply to Al Amin Biswas

Re: Why ROC is important?

by Humaira Yasmin Aliza -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Syed Mahiuddin -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Shakil Khan -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Sumaiya Mustari Mim -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests
In reply to Al Amin Biswas

Re: Why ROC is important?

by Saif Al Mahmud -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Merazul Islam Meraz -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:

True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Kazi Aahala Nagary -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:
True Positive Rate
False Positive Rate
In reply to Al Amin Biswas

Re: Why ROC is important?

by Tariqul Islam -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Soriful Alam Shetu(191-15-2408) -
ROC curves are used in clinical biochemistry to choose the most appropriate cut-off for a test. ... As the area under an ROC curve is a measure of the usefulness of a test in general, where a greater area means a more useful test, the areas under ROC curves are used to compare the usefulness of tests.
In reply to Al Amin Biswas

Re: Why ROC is important?

by Deepanita Baidya -
An ROC curve (receiver operating characteristic curve) is a graph showing the performance of a classification model at all classification thresholds. This curve plots two parameters:
True Positive Rate
False Positive Rate