<jupyter_start><jupyter_text>build_stateless_mean(bsm) VS build_aggregate_and_clip(bac)<jupyter_code>data.head()


data.plot.scatter('test_metrics accuracy(bsm)','test_metrics accuracy(bac)')



data.plot.scatter('test_metrics_target accuracy(bsm)','test_metrics_target accuracy(bac)')



data.plot.scatter('loss1(bsm)','loss1(bac)')




data.plot.scatter('loss2(bsm)','loss2(bac)')


data['norm_bound']<jupyter_output><empty_output><jupyter_text>WHEN NORM_BOUND = 0.33<jupyter_code>X = data
X = X.drop(data[data['norm_bound'] !=0.33].index)
X.plot.scatter('test_metrics_target accuracy(bsm)','test_metrics_target accuracy(bac)')

X.plot.scatter('test_metrics accuracy(bsm)','test_metrics accuracy(bac)')

X.plot.scatter('loss1(bsm)','loss1(bac)')

X.plot.scatter('loss2(bsm)','loss2(bac)')<jupyter_output><empty_output><jupyter_text>WHEN NORM_BOUND = 0.15<jupyter_code>X = data
X = X.drop(data[data['norm_bound'] !=0.15].index)

X.plot.scatter('test_metrics_target accuracy(bsm)','test_metrics_target accuracy(bac)')

X.plot.scatter('test_metrics accuracy(bsm)','test_metrics accuracy(bac)')

X.plot.scatter('loss1(bsm)','loss1(bac)')

X.plot.scatter('loss2(bsm)','loss2(bac)')<jupyter_output><empty_output><jupyter_text>WHEN NORM_BOUND = 0.25<jupyter_code>X = data
X = X.drop(data[data['norm_bound'] !=0.25].index)

X.plot.scatter('test_metrics_target accuracy(bsm)','test_metrics_target accuracy(bac)')

X.plot.scatter('test_metrics accuracy(bsm)','test_metrics accuracy(bac)')

X.plot.scatter('loss1(bsm)','loss1(bac)')

X.plot.scatter('loss2(bsm)','loss2(bac)')<jupyter_output><empty_output><jupyter_text>WHEN NORM_BOUND = 0.5<jupyter_code>X = data
X = X.drop(data[data['norm_bound'] !=0.5].index)

X.plot.scatter('test_metrics_target accuracy(bsm)','test_metrics_target accuracy(bac)')

X.plot.scatter('test_metrics accuracy(bsm)','test_metrics accuracy(bac)')

X.plot.scatter('loss1(bsm)','loss1(bac)')

X.plot.scatter('loss2(bsm)','loss2(bac)')<jupyter_output><empty_output>
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