Datasets:

DaniFrame
/

AFRLA-assessor-instance-level-results

index int64 0 256k	L1s_real float64 -14.74 15.1	L1_real float64 0 15.1	L2s_real float64 -217.31 227	L2_real float64 0 227	Lpls_real float64 -1 1	Lpl_real float64 0 1	L1s_prediction float64 -2.47 3.11	L1_prediction float64 -1.13 5.49	L2s_prediction float64 -14.75 17.4	L2_prediction float64 -11.98 30.1	Lpls_prediction float64 -0.48 0.64	Lpl_prediction float64 -0.03 1.02
0	-0.433971	0.433971	-0.188331	0.188331	-0.14754	0.14754	-0.232144	1.756522	-2.466874	6.030414	-0.005799	0.439715
1	-0.021408	0.021408	-0.000458	0.000458	-0.007332	0.007332	0.154809	2.000029	-1.24359	7.31355	0.089877	0.48754
2	2.110844	2.110844	4.455662	4.455662	0.618711	0.618711	-0.043024	1.639788	-1.317369	5.337839	0.027273	0.417921
3	0.482685	0.482685	0.232985	0.232985	0.163819	0.163819	0.335774	1.277652	-0.115386	2.954824	0.11968	0.367573
4	0.942024	0.942024	0.887409	0.887409	0.311875	0.311875	-0.016333	1.559114	-1.98336	4.085974	0.059816	0.429266
5	-1.080873	1.080873	-1.168286	1.168286	-0.354143	0.354143	0.000261	1.116913	-1.562187	1.647138	0.051681	0.349118
6	-5.506159	5.506159	-30.317787	30.317787	-0.954999	0.954999	-0.384737	1.974764	-3.025888	6.937162	-0.030062	0.482245
7	-0.031466	0.031466	-0.00099	0.00099	-0.010776	0.010776	-0.13746	1.502202	-1.794013	4.264724	0.012464	0.400376
8	-3.124965	3.124965	-9.765406	9.765406	-0.789547	0.789547	0.229615	1.791506	-0.754064	5.882746	0.105953	0.457132
9	1.222986	1.222986	1.495695	1.495695	0.395956	0.395956	0.190157	1.192667	-0.693786	2.751808	0.090221	0.342609
10	-0.215598	0.215598	-0.046482	0.046482	-0.073703	0.073703	0.238711	1.435016	-0.912448	4.065323	0.107402	0.390854
11	2.62645	2.62645	6.89824	6.89824	0.716053	0.716053	-0.067851	2.039616	-2.200552	7.267297	0.04666	0.501301
12	1.961788	1.961788	3.848612	3.848612	0.586206	0.586206	-0.126084	1.681854	-1.982586	5.467411	0.01562	0.432213
13	2.496401	2.496401	6.232018	6.232018	0.693651	0.693651	-0.414979	2.249656	-3.382584	9.213477	-0.046033	0.517342
14	1.15231	1.15231	1.327818	1.327818	0.375353	0.375353	-0.142534	2.24918	-2.777965	8.819776	0.032087	0.530255
15	-4.343562	4.343562	-18.866531	18.866531	-0.902876	0.902876	-0.08578	2.362801	-2.692339	9.451199	0.052983	0.548078
16	0.875035	0.875035	0.765686	0.765686	0.291019	0.291019	-0.450876	2.118084	-4.010604	8.055501	-0.037792	0.506341
17	0.887986	0.887986	0.788519	0.788519	0.295073	0.295073	0.150843	1.799871	-1.563975	5.900881	0.100682	0.46057
18	-3.225615	3.225615	-10.404592	10.404592	-0.80218	0.80218	-0.364693	2.75117	-3.70509	12.437599	-0.022419	0.596359
19	-1.485991	1.485991	-2.208169	2.208169	-0.469101	0.469101	-0.131538	1.931642	-2.506625	7.179878	0.027388	0.467726
20	-0.700373	0.700373	-0.490522	0.490522	-0.235365	0.235365	0.285108	1.001364	0.03507	1.628891	0.101957	0.309056
21	0.887986	0.887986	0.788519	0.788519	0.295073	0.295073	-0.304562	2.133782	-2.808903	8.502312	-0.023499	0.497099
22	-3.111275	3.111275	-9.680032	9.680032	-0.787774	0.787774	-0.229021	2.212501	-2.914157	8.548074	0.010372	0.52281
23	1.222986	1.222986	1.495695	1.495695	0.395956	0.395956	0.267784	1.165581	-0.487464	2.483198	0.112542	0.339869
24	1.05049	1.05049	1.103529	1.103529	0.34501	0.34501	0.370353	1.462222	-0.253495	3.743171	0.142195	0.403742
25	-4.086629	4.086629	-16.700537	16.700537	-0.88526	0.88526	-0.300375	2.596005	-3.242467	11.236876	-0.009801	0.577477
26	-0.518572	0.518572	-0.268917	0.268917	-0.175755	0.175755	-0.366208	1.879747	-3.183196	6.699619	-0.030901	0.464149
27	-1.948453	1.948453	-3.796469	3.796469	-0.5832	0.5832	-0.033204	2.054167	-1.920956	7.76342	0.044923	0.493614
28	-5.61047	5.61047	-31.477374	31.477374	-0.958037	0.958037	1.122508	5.354496	2.628029	29.098897	0.292948	1.00515
29	3.859866	3.859866	14.898566	14.898566	0.867259	0.867259	0.249925	2.007558	-1.312945	7.197945	0.12511	0.495061
30	1.762648	1.762648	3.106927	3.106927	0.539653	0.539653	0.675971	0.757465	1.962096	-0.052585	0.186741	0.268937
31	-0.091975	0.091975	-0.008459	0.008459	-0.031489	0.031489	0.166435	1.193726	-0.691069	2.645451	0.08576	0.342914
32	0.87137	0.87137	0.759286	0.759286	0.289869	0.289869	0.811409	1.280759	2.839048	3.458113	0.203864	0.350792
33	-4.630754	4.630754	-21.443883	21.443883	-0.919522	0.919522	-0.175022	1.706873	-2.702448	5.85792	0.018433	0.430417
34	-1.418986	1.418986	-2.013521	2.013521	-0.451011	0.451011	-0.265842	2.907281	-4.159547	12.888749	0.025916	0.638133
35	-4.371765	4.371765	-19.112329	19.112329	-0.904646	0.904646	-0.334999	2.405948	-4.380255	9.700584	0.010775	0.558773
36	-2.124965	2.124965	-4.515476	4.515476	-0.621687	0.621687	-0.310086	2.073772	-2.924954	8.134334	-0.022416	0.488395
37	-3.062651	3.062651	-9.379831	9.379831	-0.781373	0.781373	-0.297029	1.604678	-3.590398	5.352175	0.003707	0.409416
38	5.698105	5.698105	32.468401	32.468401	0.960433	0.960433	0.866742	0.742925	3.115504	-0.052216	0.224458	0.257546
39	-1.841909	1.841909	-3.392629	3.392629	-0.55861	0.55861	0.24378	1.159671	-0.519702	2.53346	0.104206	0.336426
40	-6.203192	6.203192	-38.479591	38.479591	-0.971842	0.971842	-0.296976	3.148978	-4.11251	15.081467	0.006842	0.658276
41	-2.709987	2.709987	-7.34403	7.34403	-0.72971	0.72971	-0.302448	1.881765	-3.445268	6.357323	0.002768	0.472819
42	-9.644245	9.644245	-93.011462	93.011462	-0.997299	0.997299	-0.45781	3.147431	-4.942206	15.219086	-0.021355	0.649936
43	0.274063	0.274063	0.075111	0.075111	0.093585	0.093585	-0.291195	2.316193	-3.138681	9.193931	-0.005226	0.53966
44	-2.84769	2.84769	-8.109338	8.109338	-0.75101	0.75101	-0.355235	2.78904	-5.086877	12.505457	0.015303	0.609732
45	-13.438237	13.438237	-180.586214	180.586214	-0.999799	0.999799	-0.7512	3.080815	-6.081798	14.515961	-0.090485	0.651403
46	0.110844	0.110844	0.012286	0.012286	0.037943	0.037943	0.224618	1.483988	-0.791098	3.812514	0.107369	0.410326
47	-1.343562	1.343562	-1.805159	1.805159	-0.430197	0.430197	-0.169505	2.861299	-3.573788	12.730495	0.042152	0.627324
48	2.968534	2.968534	8.812194	8.812194	0.7685	0.7685	0.154088	1.486639	-1.012983	4.191558	0.085296	0.401245
49	2.698105	2.698105	7.279771	7.279771	0.727802	0.727802	0.519103	1.010771	0.769334	1.544069	0.166134	0.309753
50	0.492581	0.492581	0.242636	0.242636	0.167115	0.167115	-1.00384	3.964954	-7.818486	19.434488	-0.124664	0.808289
51	-3.37355	3.37355	-11.38084	11.38084	-0.819522	0.819522	-0.778808	2.073212	-5.70243	7.698118	-0.103758	0.500225
52	2.158091	2.158091	4.657357	4.657357	0.628598	0.628598	0.08075	1.363883	-1.526437	3.850586	0.076274	0.368137
53	2.719865	2.719865	7.397667	7.397667	0.731288	0.731288	0.533974	0.919904	1.328082	1.055806	0.157143	0.290705
54	0.222986	0.222986	0.049723	0.049723	0.076219	0.076219	0.153196	1.347722	-0.84508	3.799426	0.081996	0.363847
55	-1.327403	1.327403	-1.761999	1.761999	-0.425676	0.425676	-0.129749	2.019565	-2.675423	7.348003	0.033522	0.494703
56	-3.290461	3.290461	-10.827134	10.827134	-0.809957	0.809957	-1.116658	4.617011	-7.829075	23.664714	-0.163631	0.904244
57	-2.506159	2.506159	-6.280833	6.280833	-0.695381	0.695381	0.005357	1.381492	-1.951541	3.37997	0.065068	0.388889
58	-1.506159	1.506159	-2.268515	2.268515	-0.47447	0.47447	0.087382	1.391677	-1.778851	3.457963	0.086225	0.39147
59	-11.124965	11.124965	-123.764846	123.764846	-0.999019	0.999019	-0.355152	2.44495	-4.682946	10.011063	0.009595	0.565235
60	-5.506159	5.506159	-30.317787	30.317787	-0.954999	0.954999	-0.923634	2.214402	-6.100836	8.711793	-0.138236	0.5175
61	-7.138567	7.138567	-50.959139	50.959139	-0.985063	0.985063	-1.648308	2.629689	-10.905697	10.772699	-0.244852	0.594933
62	-0.343562	0.343562	-0.118035	0.118035	-0.117122	0.117122	0.099477	2.163613	-1.217877	8.145797	0.074904	0.518381
63	-5.3448	5.3448	-28.566887	28.566887	-0.949872	0.949872	-0.369637	2.007666	-3.353875	6.958187	-0.021218	0.497531
64	-7.893537	7.893537	-62.307926	62.307926	-0.991067	0.991067	-0.153387	2.083048	-1.666581	8.098702	-0.001561	0.493018
65	-5.026794	5.026794	-25.268658	25.268658	-0.93805	0.93805	-0.694862	2.153364	-4.954283	8.172781	-0.086208	0.508871
66	-2.49902	2.49902	-6.245101	6.245101	-0.694116	0.694116	-0.558856	2.522019	-4.058794	10.412447	-0.069376	0.574453
67	-8.131783	8.131783	-66.125895	66.125895	-0.992407	0.992407	0.254564	2.958029	-0.929916	13.488868	0.115783	0.634493
68	-3.017543	3.017543	-9.105566	9.105566	-0.775283	0.775283	-0.228035	2.676374	-3.108171	12.069579	0.006727	0.582755
69	0.059972	0.059972	0.003597	0.003597	0.020536	0.020536	-0.121223	1.642481	-1.982273	5.398881	0.019151	0.419666
70	-1.649594	1.649594	-2.72116	2.72116	-0.511639	0.511639	0.114136	1.198358	-0.954062	2.906129	0.071652	0.339779
71	-0.279384	0.279384	-0.078055	0.078055	-0.095391	0.095391	0.036917	1.554539	-1.400416	4.83757	0.055157	0.406647
72	-0.084359	0.084359	-0.007116	0.007116	-0.028883	0.028883	0.16585	1.682098	-0.986151	5.171469	0.092372	0.439846
73	-2.191775	2.191775	-4.803878	4.803878	-0.635525	0.635525	0.02205	1.460039	-1.396129	4.476371	0.053081	0.382719
74	0.481428	0.481428	0.231773	0.231773	0.1634	0.1634	0.345983	1.766927	-0.222296	5.713423	0.131838	0.453773
75	-0.417235	0.417235	-0.174085	0.174085	-0.141928	0.141928	0.12526	1.731969	-0.974142	5.967553	0.072233	0.435402
76	-4.475091	4.475091	-20.026439	20.026439	-0.910871	0.910871	-0.631394	2.266845	-4.319343	9.268719	-0.089047	0.519695
77	-3.630754	3.630754	-13.182375	13.182375	-0.846436	0.846436	-0.280432	1.6255	-1.997958	5.24842	-0.032783	0.415775
78	-2.753137	2.753137	-7.579763	7.579763	-0.736545	0.736545	-0.107607	2.326799	-2.689671	9.502398	0.042916	0.535274
79	-4.017543	4.017543	-16.140652	16.140652	-0.880033	0.880033	-0.30896	2.680415	-3.573986	11.623976	-0.005036	0.596849
80	-1.991437	1.991437	-3.965821	3.965821	-0.592831	0.592831	-0.118888	1.328536	-2.013974	3.46669	0.023811	0.367853
81	-9.120847	9.120847	-83.18985	83.18985	-0.996136	0.996136	-0.15459	2.0316	-2.580759	7.925409	0.019199	0.481703
82	-4.149065	4.149065	-17.21474	17.21474	-0.889798	0.889798	-0.261886	1.514804	-2.625529	4.680108	-0.00871	0.395315
83	-1.70978	1.70978	-2.923348	2.923348	-0.526694	0.526694	-0.534306	2.560336	-4.637159	11.079505	-0.052266	0.571143
84	-1.639821	1.639821	-2.689013	2.689013	-0.509164	0.509164	0.183814	1.365561	-1.098559	3.802269	0.099361	0.371297
85	-3.753137	3.753137	-14.086037	14.086037	-0.857907	0.857907	-0.458399	2.479102	-3.968591	10.394125	-0.039482	0.561241
86	-0.639821	0.639821	-0.409371	0.409371	-0.215683	0.215683	0.053445	1.458484	-1.57971	4.385541	0.068432	0.385745
87	-1.56318	1.56318	-2.443532	2.443532	-0.489462	0.489462	0.135876	1.325312	-1.316497	3.594666	0.087293	0.364852
88	-5.007017	5.007017	-25.070219	25.070219	-0.937232	0.937232	-0.640761	2.173527	-4.948053	8.726515	-0.074575	0.504473
89	0.642607	0.642607	0.412944	0.412944	0.216592	0.216592	-0.078872	2.064369	-2.630663	7.308899	0.054574	0.508875
90	2.568979	2.568979	6.599655	6.599655	0.706327	0.706327	0.542449	1.350661	0.49873	2.988766	0.179974	0.387201
91	4.05049	4.05049	16.406469	16.406469	0.882553	0.882553	0.348902	1.333077	-0.219766	3.189584	0.129613	0.377526
92	3.834942	3.834942	14.70678	14.70678	0.865127	0.865127	0.258932	1.477542	-0.851741	3.849835	0.119227	0.407876
93	-3.433971	3.433971	-11.792157	11.792157	-0.826203	0.826203	-0.054086	1.775246	-2.604042	5.658209	0.060447	0.459287
94	-1.23206	1.23206	-1.517971	1.517971	-0.398573	0.398573	-0.469013	1.801069	-4.106211	6.375297	-0.03977	0.446719
95	-5.476682	5.476682	-29.994046	29.994046	-0.954102	0.954102	-0.105962	1.844525	-2.280266	6.504483	0.029346	0.458342
96	-0.829985	0.829985	-0.688875	0.688875	-0.276834	0.276834	0.286677	1.314763	-0.005285	3.141186	0.105828	0.368658
97	1.523318	1.523318	2.320498	2.320498	0.479011	0.479011	0.050278	1.696062	-1.675034	5.239411	0.070336	0.443065
98	-1.165058	1.165058	-1.35736	1.35736	-0.379097	0.379097	0.295881	1.23934	0.21252	2.684606	0.100671	0.358077
99	-3.56318	3.56318	-12.696252	12.696252	-0.839744	0.839744	-0.151257	1.285935	-2.747595	3.127987	0.032769	0.363845

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Assessors For Regression: Loss Analysis - Assessor Instance Level Results

Instance level results for assessors models trained on the AFRLA - Instance Level Results dataset.

At the moment of upload, results for XGBoost and linear regression models are available, with results from the former in 5 different seeds. Results are available for all 11 tasks described in the original dataset as well as for 6 different types of error (losses):

Loss name	Description	Formula
L₁ ^∓	Difference error with sign	ŷ - y
L₁ ⁺	Absolute error	\|ŷ - y\|
L₂ ^∓	Squared error with sign	(ŷ - y)²
L₂ ⁺	Squared error	(ŷ - y)² · sgn(ŷ - y)
L_L ^∓	Logistic error with sign parametrised by a value β so that the mean absolute error is 0.5	2 / (1+e^{-β(ŷ - y)}) - 1
L_L ⁺	Absolute logistic error parametrised by a value β so that the mean absolute error is 0.5	\|2 / (1+e^{-β(ŷ - y)}) - 1\|

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Number of rows:

47,140,830