Diversity prediction theorem: Difference between revisions
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crowd-error : 4.00000
diversity : 10.50000
</pre>
=={{header|ALGOL 68}}==
{{Trans|Phix}}
<syntaxhighlight lang="algol68">
BEGIN # Diversity Prediction Theorem #
# utility operators #
OP LENGTH = ( []REAL a )INT: ( UPB a - LWB a ) + 1;
OP LENGTH = ( STRING a )INT: ( UPB a - LWB a ) + 1;
OP SUM = ( []REAL a )REAL:
BEGIN
REAL result := 0;
FOR i FROM LWB a TO UPB a DO result +:= a[ i ] OD;
result
END # SUM # ;
PRIO PAD = 9;
OP PAD = ( INT width, STRING v )STRING: # left blank pad v to width #
IF LENGTH v >= width THEN v ELSE ( " " * ( width - LENGTH v ) ) + v FI;
OP - = ( []REAL a, REAL v )[]REAL: # return a with elements - v #
BEGIN
[ LWB a : UPB a ]REAL result;
FOR i FROM LWB a TO UPB a DO result[ i ] := v - a[ i ] OD;
result
END # - # ;
OP ^ = ( []REAL a, INT p )[]REAL: # return a with elements raised to p #
BEGIN
[ LWB a : UPB a ]REAL result;
FOR i FROM LWB a TO UPB a DO result[ i ] := a[ i ] ^ p OD;
result
END # |^ # ;
PRIO FMT = 1;
OP FMT = ( REAL v, INT d )STRING: # formats v with up to d decimals #
BEGIN
STRING result := fixed( v, -0, d );
IF result[ LWB result ] = "." THEN "0" +=: result FI;
WHILE result[ UPB result ] = "0" DO result := result[ : UPB result - 1 ] OD;
IF result[ UPB result ] = "." THEN result := result[ : UPB result - 1 ] FI;
" " + result
END # FMT # ;
# task #
MODE NAMEDVALUE = STRUCT( STRING name, REAL value );
PROC mean = ( []REAL s )REAL: SUM s / LENGTH s;
PROC variance = ( []REAL s, REAL d )REAL: mean( ( s - d ) ^ 2 );
PROC diversity theorem = ( REAL reference, []REAL observations )[]NAMEDVALUE:
BEGIN
REAL average = mean( observations );
( ( "average_error", variance( observations, reference ) )
, ( "crowd_error", ( reference - average ) ^ 2 )
, ( "diversity", variance( observations, average ) )
)
END # diversity theorem # ;
PROC test = ( REAL reference, []REAL observations )VOID:
BEGIN
[]NAMEDVALUE res = diversity theorem( reference, observations );
FOR i FROM LWB res TO UPB res DO
print( ( 14 PAD name OF res[ i ], " : ", value OF res[ i ] FMT 6, newline ) )
OD
END # test # ;
test( 49, ( 48, 47, 51 ) );
test( 49, ( 48, 47, 51, 42 ) )
END
</syntaxhighlight>
{{out}}
<pre>
average_error : 3
crowd_error : 0.111111
diversity : 2.888889
average_error : 14.5
crowd_error : 4
diversity : 10.5
</pre>
Line 704 ⟶ 783:
crowd-error: 4
diversity: 10.5</pre>
=={{header|EasyLang}}==
{{trans|BASIC256}}
<syntaxhighlight>
proc calc TrueVal test[] . .
for test in test[]
h = (test - TrueVal)
Vari += h * h
Sum += test
c += 1
.
AvgErr = Vari / c
RefAvg = Sum / c
h = (TrueVal - RefAvg)
CrowdErr = h * h
print "Average error : " & AvgErr
print " Crowd error : " & CrowdErr
print " Diversity : " & AvgErr - CrowdErr
print ""
.
calc 49 [ 48 47 51 ]
calc 49 [ 48 47 51 42 ]
</syntaxhighlight>
=={{header|Factor}}==
Line 1,851 ⟶ 1,953:
the crowd error: 4
prediction diversity: 10.5
</pre>
=={{header|RPL}}==
{{works with|HP|48G}}
{| class="wikitable" ≪
! RPL code
! Comment
|-
|
« → pivot
« 1 « pivot - SQ » DOLIST
∑LIST LASTARG SIZE /
» » '<span style="color:blue">SQDIF</span>' STO
« → preds truth
« preds truth <span style="color:blue">SQDIF</span> "avg_err" →TAG
preds ∑LIST LASTARG SIZE /
DUP truth - SQ "cwd_err" →TAG
preds ROT <span style="color:blue">SQDIF</span> "pred_div" →TAG
3 →LIST
» » '<span style="color:blue">CROWD</span>' STO
|
<span style="color:blue">SQDIF</span> ( { values } pivot → average((value-pivot)²) )
get (value-pivot)²
get average
<span style="color:blue">CROWD</span> ( { preds } truth → { report } )
avg_err = mean((pred-truth)²)
average = ∑preds / number of preds
cwd_err = (average-truth)²
prd_div = mean((pred-cwd_err)²)
put them all into a list
|}
{ 48 47 51 } 49 <span style="color:blue">CROWD</span>
{ 48 47 51 42 } 49 <span style="color:blue">CROWD</span>
{{out}}
<pre>
2: { avg_err:3 cwd_err:0.111111111111 pred_div:2.88888888889 }
1: { avg_err:14.5 cwd_err:4 pred_div:10.5 }
</pre>
Line 1,986 ⟶ 2,129:
=={{header|Wren}}==
{{trans|Go}}
<syntaxhighlight lang="
var averageSquareDiff = Fn.new { |f, preds|
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