alan-turing-institute / MLJTuning.jl / 78

Committed 11 Mar 2020 - 4:26 coverage: 80.455% (-3.2%) from 83.613%

Build # 78

Build Type

Pull #19

travis-ci-com

Committed by

web-flow

Commit Message

bump to 0.2.0 and bump [compat] MLJBase = "^0.12"

Pull Request Pull Request #19: Update to MLJBase 0.12.0

Run Details

177 of 220 relevant lines covered (80.45%)

205.54 hits per line

Source File
Press 'n' to go to next uncovered line, 'b' for previous

66.67

/src/tuning_strategy_interface.jl

abstract type TuningStrategy <: MLJBase.MLJType end
MLJBase.show_as_constructed(::Type{<:TuningStrategy}) = true

# for initialization of state (compulsory)
setup(tuning::TuningStrategy, model, range, verbosity) = range

# for building each element of the history:
result(tuning::TuningStrategy, history, e) =
    (measure=e.measure, measurement=e.measurement)

# for generating batches of new models and updating the state (but not
# history):
function models! end

# for extracting the optimal model (and its performance) from the
# history:
function best(tuning::TuningStrategy, history)
   measurements = [h[2].measurement[1] for h in history]
   measure = first(history)[2].measure[1]
   if orientation(measure) == :score
       measurements = -measurements
   end
   best_index = argmin(measurements)
   return history[best_index]
end

# for selecting what to report to the user apart from the optimal
# model:
tuning_report(tuning::TuningStrategy, history, state) = (history=history,)

# for declaring the default number of models to evaluate:
default_n(tuning::TuningStrategy, range) = 10

1	abstract type TuningStrategy <: MLJBase.MLJType end
2	MLJBase.show_as_constructed(::Type{<:TuningStrategy}) = true	!
3
4	# for initialization of state (compulsory)
UNCOV 5	setup(tuning::TuningStrategy, model, range, verbosity) = range	!
6
7	# for building each element of the history:
8	result(tuning::TuningStrategy, history, e) =	2,770×
9	(measure=e.measure, measurement=e.measurement)
10
11	# for generating batches of new models and updating the state (but not
12	# history):
13	function models! end
14
15	# for extracting the optimal model (and its performance) from the
16	# history:
17	function best(tuning::TuningStrategy, history)
18	measurements = [h[2].measurement[1] for h in history]	369×
19	measure = first(history)[2].measure[1]
20	if orientation(measure) == :score	147×
21	measurements = -measurements
22	end
23	best_index = argmin(measurements)	1,152×
24	return history[best_index]	123×
25	end
26
27	# for selecting what to report to the user apart from the optimal
28	# model:
29	tuning_report(tuning::TuningStrategy, history, state) = (history=history,)	64×
30
31	# for declaring the default number of models to evaluate:
32	default_n(tuning::TuningStrategy, range) = 10	!

alan-turing-institute / MLJTuning.jl / 78

Source File Press 'n' to go to next uncovered line, 'b' for previous

Source File
Press 'n' to go to next uncovered line, 'b' for previous