To ensure that the Autoencoder model shown in Figure learns the desired patterns effectively, the model should consider only the auxetic materials as exceptions. Hence we clean the data based on the widely used protocol of removing points below Q1 -1.5*IQR(Interquartile range) or above Q3+1.5*IQR of the features. Where Q1, Q3, and IQR are 25th percentile, 75th percentile, and Q3-Q1 respectively. For example, materials with energy above convex hull less than 80 meV (stability criteria) are retained. Moreover, substances having lower than 46 computationally traceable sites are kept (natcomm). More details of the cleaning are provided in . The reduced set containing 15 auxetic materials and 4476 normal samples with 60 descriptors (discussed later) are fed into the model.