And it adds a - priori information into the patterns to change the method as a semi - supervised clustering . in the clustering process , the unlabelled patterns compare similarities with the labeled patterns , and then the accuracy of the algorithm can be increased . ( 3 ) the paper proposes an interactive learning - based image mining in remote sensing 由于遙感圖像各類別在特征空間中散點(diǎn)圖的分布的特點(diǎn),本文對傳統(tǒng)的fcm聚類算法進(jìn)行改進(jìn),并且加入先驗(yàn)信息之后,將原來的非監(jiān)督的聚類變成一種半監(jiān)督的聚類方法,通過與已標(biāo)簽的樣本進(jìn)行相似性比較,能有效地提高聚類算法的準(zhǔn)確度。