# Image Classification on Breast Histopathology binary: IDC vs. non-IDC

Source: [Image Classification on Breast Histopathology binary: IDC vs. non-IDC](<https://www.sota2.com/research/sota/image-classification-on-breast-histopathology-binary-idc-vs-non-idc>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-03-27T12:18:20.646Z

Evaluation of Image Classification performance on the Breast Histopathology dataset focusing on the binary distinction between IDC and non-IDC cases, reporting Accuracy (Acc) and Negative Log Likelihood (NLL).

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

| Scope | Recorded value |
| --- | --- |
| Task | Image Classification |
| Dataset (including any stated split) | Breast Histopathology binary: IDC vs. non-IDC |
| Metric | Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 5 of 5 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [Accuracy](<https://www.sota2.com/research/sota/image-classification-on-breast-histopathology-binary-idc-vs-non-idc.md?metric=Accuracy>): Higher is better; unit: PERCENT.

- [NLL](<https://www.sota2.com/research/sota/image-classification-on-breast-histopathology-binary-idc-vs-non-idc.md?metric=NLL>): Lower is better; unit: SCALAR.

## Recorded results

| Method | Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| GM | 84.5 | Not recorded | 691ea0a8d6b0dd334292e06a |
| kNN | 84 | Not recorded | 691ea0a8d6b0dd334292e06a |
| Linear | 83.6 | Not recorded | 691ea0a8d6b0dd334292e06a |
| Label Spreading | 82.6 | Not recorded | 691ea0a8d6b0dd334292e06a |
| kNN-budget | 79.7 | Not recorded | 691ea0a8d6b0dd334292e06a |

### GM

Accuracy: 84.5. Result ID: 69c6756847f34ce924b032d6.

[Reporting paper](<https://www.sota2.com/research/paper/691ea0a8d6b0dd334292e06a.md>)

[Method origin paper](<https://www.sota2.com/research/paper/691ea0a8d6b0dd334292e06a.md>)

Recorded evaluation configuration: {"Encoder":"ResNet18","P (number of prototypes)":"32"}. This record does not assert independent reproduction.

### kNN

Accuracy: 84. Result ID: 69c6756847f34ce924b032d8.

[Reporting paper](<https://www.sota2.com/research/paper/691ea0a8d6b0dd334292e06a.md>)

Recorded evaluation configuration: {"Encoder":"ResNet18"}. This record does not assert independent reproduction.

### Linear

Accuracy: 83.6. Result ID: 69c6756847f34ce924b032da.

[Reporting paper](<https://www.sota2.com/research/paper/691ea0a8d6b0dd334292e06a.md>)

Recorded evaluation configuration: {"Encoder":"ResNet18"}. This record does not assert independent reproduction.

### Label Spreading

Accuracy: 82.6. Result ID: 69c6756847f34ce924b032d9.

[Reporting paper](<https://www.sota2.com/research/paper/691ea0a8d6b0dd334292e06a.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa646e1e209131cea04ae5.md>)

Recorded evaluation configuration: {"Encoder":"ResNet18"}. This record does not assert independent reproduction.

### kNN-budget

Accuracy: 79.7. Result ID: 69c6756847f34ce924b032d7.

[Reporting paper](<https://www.sota2.com/research/paper/691ea0a8d6b0dd334292e06a.md>)

Recorded evaluation configuration: {"Encoder":"ResNet18","P (number of prototypes)":"32"}. This record does not assert independent reproduction.

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