Even though the original Kepler mission ended due to mechanical failures, the Kepler satellite continues to collect data. Using classification models, we can understand the features exoplanets possess and then use those features to investigate further for any more information on the candidate planet. Based on the classification model, the idea is to find out the probability of the planet under observation being a candidate for an exoplanet or a false positive. If the model predicts that the observation is a candidate for being an exoplanet, then the further investigation can be conducted. From the model, we can narrow down the features that might explain the difference between a candidate and a false-positive which ultimately helps us to increase the efficiency of any model and fine-tune the model and ultimately the process of searching for any future exoplanets. The model comparison is supported by McNemar's test for checking significance.
翻译:尽管最初的开普勒任务因机械故障而终止,但开普勒卫星仍继续收集数据。使用分类模型,我们可以理解外行星具有的特征,然后利用这些特征进一步调查有关候选行星的任何更多信息。根据分类模型,我们的想法是找出观察中的地球作为候选异行星或假阳性的概率。如果模型预测观察是候选异行星,那么可以进行进一步调查。从模型中,我们可以缩小可能解释候选人与假阳性之间的差别的特征,最终帮助我们提高任何模型的效率,微调模型并最终搜索未来任何外行星的过程。模型的比较得到了McNemar测试的支持,以检验其重要性。