Publication
Early detection of ovarian cancer is crucial for a good outlook. Different machine learning methods have already proven useful to that effect, but using many features and samples often yields a complex structure of classifier algorithms.
This study investigates the effect of four different manifold learning methods prior to well-known classification algorithms to reduce the number of features and compares the achieved results with the well-known principal component analysis method.
The NCI PBSII dataset, which consists of 253 samples with 15154 features, is used in this study. We tested nine distinct classifiers: k-nearest neighbors, decision tree, support vector machines, stochastic gradient descent, random forest, multi-layer perceptron, Naive Bayes, logistic regression, and AdaBoost.
Among these classifiers, the logistic regression gives a maximum of 99.2% accuracy using these features. These classifiers were rerun for five distinct reduced feature sets obtained using principal component analysis, Multidimensional Scaling, Locally Linear Embedding, Isometric Feature Mapping, and t-Distributed Stochastic Neighbor Embedding methods. Among these feature reduction methods, Locally Linear Embedding hit the maximum classifier performance five times (of nine classifiers) with an average of 15.4 components. Both the logistic regression classifier with 28 Multidimensional Scaling components and the stochastic gradient descent classifier with 30 Locally Linear Embedding components achieved the maximum accuracies of 99.8%. On the other hand, the commonly used principal component analysis resulted in a maximum of 99.7% accuracy using stochastic gradient descent with 30 principles.
In conclusion, although principal component analysis is the most commonly used feature reduction method, the Locally Linear Embedding (a manifold learning method) may give higher classifier performances with fewer components in the diagnosis of ovarian cancer.
B. Yesilkaya, M. Perc, Y. Isler, Manifold learning methods for the diagnosis of ovarian cancer, Journal of Computational Science 63 (2022) 101775.
Related
Signup
Cookie | Duration | Description |
---|---|---|
cookielawinfo-checkbox-analytics | 1 year | Set by the GDPR Cookie Consent plugin, this cookie records the user consent for the cookies in the "Analytics" category. |
cookielawinfo-checkbox-functional | 1 year | The GDPR Cookie Consent plugin sets the cookie to record the user consent for the cookies in the category "Functional". |
cookielawinfo-checkbox-necessary | 1 year | Set by the GDPR Cookie Consent plugin, this cookie records the user consent for the cookies in the "Necessary" category. |
CookieLawInfoConsent | 1 year | CookieYes sets this cookie to record the default button state of the corresponding category and the status of CCPA. It works only in coordination with the primary cookie. |
PHPSESSID | session | This cookie is native to PHP applications. The cookie stores and identifies a user's unique session ID to manage user sessions on the website. The cookie is a session cookie and will be deleted when all the browser windows are closed. |
viewed_cookie_policy | 1 year | The GDPR Cookie Consent plugin sets the cookie to store whether or not the user has consented to use cookies. It does not store any personal data. |
Cookie | Duration | Description |
---|---|---|
mec_cart | 1 month | Provides functionality for our ticket shop |
VISITOR_INFO1_LIVE | 6 months | YouTube sets this cookie to measure bandwidth, determining whether the user gets the new or old player interface. |
VISITOR_PRIVACY_METADATA | 6 months | YouTube sets this cookie to store the user's cookie consent state for the current domain. |
YSC | session | Youtube sets this cookie to track the views of embedded videos on Youtube pages. |
yt-remote-connected-devices | never | YouTube sets this cookie to store the user's video preferences using embedded YouTube videos. |
yt-remote-device-id | never | YouTube sets this cookie to store the user's video preferences using embedded YouTube videos. |
yt.innertube::nextId | never | YouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen. |
yt.innertube::requests | never | YouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen. |
Cookie | Duration | Description |
---|---|---|
_ga | 1 year | Google Analytics sets this cookie to calculate visitor, session and campaign data and track site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognise unique visitors. |
_ga_* | 1 year | Google Analytics sets this cookie to store and count page views. |
_gat_gtag_UA_* | 1 min | Google Analytics sets this cookie to store a unique user ID. |
_gid | 1 day | Google Analytics sets this cookie to store information on how visitors use a website while also creating an analytics report of the website's performance. Some of the collected data includes the number of visitors, their source, and the pages they visit anonymously. |