1. A method of training a classifier for a smoke detector, comprising: inputting sensor data from a plurality of tests into a processor, the sensor data indicative of environmental conditions during the tests; using the processor to process the sensor data from the tests to generate derived signal data corresponding to the test data for respective tests; assigning the derived signal data into categories comprising at least one fire group and at least one non-fire group; performing linear discriminant analysis (LDA) training using the processor and the derived signal data and the assigned categories for the derived signal data as input to the LDA training, the output of the LDA training generating a centroid in linear discriminant coordinates for each of the categories, a plurality of coefficients for transforming derived signal data into linear discriminant (LD) coordinates, and a mean of group means; and storing the plurality of coefficients, the plurality of centroids, and the mean of group means in a computer readable medium.