MLI will by default perform sampling if your dataset has more than 100K rows. You can disable this or set the sampling limit to a higher number through expert settings or config.toml. To increase the sampling limit:

# When number of rows are above this limit sample for MLI for scoring UI data
mli_sample_above_for_scoring = 2000000

# When number of rows are above this limit sample for MLI for training surrogate models
mli_sample_above_for_training = 200000

# When sample for MLI how many rows to sample
mli_sample_size = 200000


This will set the limit to 2000000. To disable MLI sampling:

# not only sample training, but also sample scoring
mli_sample_training = false

You will have to re-run your experiment after changing these configurations.