The structure conservation in various xcexb1-helix subclasses reveals the sequence and context dependent factors causing distortions in the xcexb1-helix. The sequence-structure relationship in these subclasses can be used to predict structural variations in xcexb1-helix purely based on its sequence. We train support vector machine(SVM) with dot product kernel function to discriminate between regular xcexb1-helix and non-regular xcexb1-helices purely based on the sequences, which are represented with various overall and position specific propensities of amino acids.