feat(clustering): palette diversifiée, suppression scores anomalie/robot, visualisation éclatée

- Suppression de 'Score Anomalie' (avg_score) des 31→30 features de clustering
- Suppression de 'Score de détection robot' (mean_score) de la sidebar et de l'API
- Suppression de bot_ips / high_risk_ips des stats (métriques dérivées des scores supprimés)
- Redistribution des poids dans risk_score_from_centroid: UA-CH mismatch +17%,
  fuzzing +14%, headless +10%, vélocité +9%, ip_id_zero +7%
- Mise à jour des indices feature dans name_cluster et risk_score_from_centroid
- Palette 24 couleurs spectrales (cluster_color) → bleu/violet/rose/teal/amber/cyan/lime...
  Les couleurs identifient les clusters, non leur niveau de risque
- Remplacement de la légende CRITICAL/HIGH/MEDIUM/LOW par la liste des clusters actifs
- Ajout de spread_clusters(): répulsion itérative des centroïdes trop proches (50 iter)
  min_dist=0.16 → les clusters se repoussent mutuellement → visualisation plus lisible
- Interface TypeScript mise à jour (suppression mean_score, bot_ips, high_risk_ips)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

frontend/src/components/ClusteringView.tsx

@@ -35,7 +35,6 @@ interface ClusterNode {
   hit_count: number;
   mean_ttl: number;
   mean_mss: number;
-  mean_score: number;
   mean_velocity: number;
   mean_fuzzing: number;
   mean_headless: number;
@@ -60,8 +59,6 @@ interface ClusterStats {
   total_clusters: number;
   total_ips: number;
   total_hits: number;
-  bot_ips: number;
-  high_risk_ips: number;
   n_samples: number;
   k: number;
   elapsed_s: number;
@@ -427,8 +424,6 @@ export default function ClusteringView() {
             <div className="font-semibold text-sm mb-2">Résultats</div>
             <Stat label="Clusters" value={data.stats.total_clusters} tooltip={TIPS.k_actual} />
             <Stat label="IPs totales" value={data.stats.total_ips.toLocaleString()} tooltip={TIPS.pca_2d} />
-            <Stat label="IPs bots 🤖" value={data.stats.bot_ips.toLocaleString()} color="text-red-400" tooltip={TIPS.ips_bots} />
-            <Stat label="Risque élevé" value={data.stats.high_risk_ips.toLocaleString()} color="text-orange-400" tooltip={TIPS.high_risk} />
             <Stat label="Hits totaux" value={data.stats.total_hits.toLocaleString()} tooltip={TIPS.total_hits} />
             <Stat label="Calcul" value={`${data.stats.elapsed_s}s`} tooltip={TIPS.calc_time} />
           </div>
@@ -504,7 +499,7 @@ export default function ClusteringView() {
             </div>
             <p className="text-white font-semibold text-lg tracking-wide">Clustering en cours…</p>
             <p className="text-text-secondary text-sm mt-1">
-              K-means++ · 31 features · {Math.round(k * sensitivity)} clusters · toutes les IPs
+              K-means++ · 30 features · {Math.round(k * sensitivity)} clusters · toutes les IPs
             </p>
             <p className="text-text-disabled text-xs mt-2 animate-pulse">Mise à jour automatique toutes les 3 secondes</p>
           </div>
@@ -527,19 +522,18 @@ export default function ClusteringView() {
             {/* Légende overlay */}
             <div style={{ position: 'absolute', bottom: 16, left: 16, pointerEvents: 'all' }}>
               <div className="bg-black/70 rounded-lg p-2 text-xs flex flex-col gap-1">
-                {([
-                  ['#dc2626', 'CRITICAL', TIPS.risk_critical],
-                  ['#f97316', 'HIGH',     TIPS.risk_high],
-                  ['#eab308', 'MEDIUM',   TIPS.risk_medium],
-                  ['#22c55e', 'LOW',      TIPS.risk_low],
-                ] as const).map(([c, l, tip]) => (
-                  <div key={l} className="flex items-center gap-2" title={tip}>
-                    <span className="w-3 h-3 rounded-full flex-shrink-0" style={{ background: c }} />
-                    <span className="text-white/80 cursor-help">{l}</span>
+                <div className="text-white/50 text-[10px] uppercase tracking-wide mb-1">Clusters</div>
+                {data?.nodes?.slice(0, 6).map((n) => (
+                  <div key={n.id} className="flex items-center gap-2">
+                    <span className="w-3 h-3 rounded-full flex-shrink-0" style={{ background: n.color }} />
+                    <span className="text-white/70 truncate max-w-[120px]">{n.label}</span>
                   </div>
                 ))}
+                {(data?.nodes?.length ?? 0) > 6 && (
+                  <div className="text-white/30 text-[10px]">+{(data?.nodes?.length ?? 0) - 6} autres…</div>
+                )}
                 <div className="mt-1 pt-1 border-t border-white/10 text-white/40 text-[10px] cursor-help" title={TIPS.features_31}>
-                  31 features · PCA 2D ⓘ
+                  30 features · PCA 2D ⓘ
                 </div>
               </div>
             </div>
@@ -666,7 +660,6 @@ function ClusterSidebar({ node, ipDetails, ipTotal, ipPage, clusterPoints, onClo
           <div className="font-semibold mb-2">Stack TCP</div>
           <Stat label="TTL moyen" value={node.mean_ttl} tooltip={TIPS.mean_ttl} />
           <Stat label="MSS moyen" value={node.mean_mss} tooltip={TIPS.mean_mss} />
-          <Stat label="Score ML" value={`${(node.mean_score * 100).toFixed(1)}%`} tooltip={TIPS.mean_score} />
           <Stat label="Vélocité" value={node.mean_velocity?.toFixed ? `${node.mean_velocity.toFixed(2)} rps` : '-'} tooltip={TIPS.mean_velocity} />
           <Stat label="Headless" value={node.mean_headless ? `${(node.mean_headless * 100).toFixed(0)}%` : '-'} tooltip={TIPS.mean_headless} />
           <Stat label="UA-CH Mismatch" value={node.mean_ua_ch ? `${(node.mean_ua_ch * 100).toFixed(0)}%` : '-'} tooltip={TIPS.mean_ua_ch} />